Carl Ernsts, Mona Siddiquis and Quran book review Essay - 1

Carl Ernsts, Mona Siddiquis and Quran book review - Essay Example ority of the Muslims, for example, the Taliban of Afghanistan and Pakistan believe that it is mandatory to fight in the name of God and kill the disbelievers. In doing so, they believe they would enter the heaven once they perish from the world. This essay will investigate the ways some of the non-Muslims and Muslims misunderstand the Quran and act upon the Holy verses. The aim of the essay is to understand the meaning of the word ‘Jihad’ and to see how Islam has been defamed in the name of the ‘Holy War.’ There are two main reasons that Islam is considered a religion that promotes terrorism. Firstly, when non-Muslims read the verses of Quran they completely ignore the fact that Quran was not only a book of guidance for people living in the past or to the people it was revealed but it is a book belonging to the people who lived in the past, are living in the present and also for the future generation to come. Secondly, some people follow the Quran word by word in a very literal sense. The Quran uses metaphors, and though it is the word of God, not every word is to be taken literally. The word Jihad is babbling not only for the non-Muslims but also for some Muslims who use and follow it in the wrong sense. The Holy Quran says â€Å"Not equal are those believers who stay behind in their homes while the believers exert in the cause of God with their wealth and life. God has kept a higher rank for those who exert in the name of God† (Quran 4:95). The believers of the book hugely misunderstand this verse. There is a misconception between some groups of people what exertion refers to. Though it is believed that it refers to Jihad, the meaning of Jihad tends to vary greatly among believers. Some of the better-known scholars of Islam like Abdullah Yousuf and Muhammad Asaddefine Jihad as a struggle or fight made to achieve justice. Jihad is a struggle made against oppression even if it means to risk one’s life. While there is some extremist groups that define

Evolution of Technology Essay Example for Free

Evolution of Technology Essay â€Å"Men are only so good as their technical developments allows them to be† (Orwell 56). When the technology boom occurred in the 1990s and beyond, a typical student’s backpack would consist of a boondoggle, leather-bound planner, pager, cassette player, 3. 5 inch floppy disk, and a hardcover textbook. Time advanced, and eventually made its way into the 2000s, when then a backpack would hold a keychain game, CD player, soft cover textbook with a CD-ROM, and a box-shaped cell phone. Technology continued to grow into the next decade with backpacks full of smart phones, laptops, graphic calculators, receipts for online textbook purchases, MP3 players, a backup charger, and a 4GB flash drive attached to the bag’s zipper. Evolution of technology has come into major play, and has begun to conquer today’s society with one discovery at a time. For example, as assembly lines become familiar to many, technology advancements closely follow. While hundreds of employees used to manually run a factory, the majority of the hard work is now done by machines, also known as artificial labor. This change has affected business owners positively, thus allowing for new positions to help run the technology and to ensure all is running well. After such advancements were formed in our society, hundreds to thousands of new companies and manufacturing plants have been built, resulting in a major increase of available jobs to the middle class, which currently, the majority of United States citizens currently occupy. Recently, IBM teamed up with Corporate Service Corps (CSC) in order to send 30 volunteers out into different countries to work on technology-related assistance, such as distance learning programs, and upgraded laser eye treatments. The fact that advanced technology can help to save millions of lives has been one of the biggest reasons for such a large demand. IBM plan to take on several projects in different countries such as India, Brazil, China, Egypt, Ghana, and more. A total of 12 teams will go into each of those countries and successfully complete the projects for better technology-based education and eye treatments, which will cost approximately $250,000 each, all paid for by IBM. The overall project has not only opened up new opportunities for those willing to add this adventurous project to their resume, but it’s also reaching out to communities in dire need, something that the latest technology has allowed to be done. Furthermore, technology has been able to expedite the process of sending aid to places I need more quickly and efficiently with the release of new features to currently existing pieces of technology, as well as software applications. Renowned author Sarah Murray explains, â€Å"When a huge earthquake hit Haiti in 2010, the addition of Haitian Creole spoken by 8m people in that country to Microsofts online translation engine, which was achieved in just five days, helped humanitarian workers who needed to be able to translate quickly. Something as simple as an online translation system, a piece of virtual technology, was able to help save thousands to millions of lives in Haiti. One of the biggest issues in aid relief is the language and unfamiliar surrounding barrier, which Microsoft has been able to defeat with the use of several applications. The company has been closely working with skilled programmers to create certain software which allow for a variety of functions, such as Twisted Pair Wave software, which allows humanitarian professionals to keep in contact with one another from any device by keeping connected to one specific network. Relief workers can then locate others in the area by sending a ping signal to the network, which helps when in an entirely new environment and unsure of the native language. Technology continues to save the lives of many, by creating jobs that allow people to continue and support their family, as well as being able to provide support for those in a life-or-death situation when it comes down to the essentials such as food, water, and housing. Some fortunate people fail to realize how difficult it really is to obtain such aid. While technology has helped to eradicate useless jobs and help to decrease labor costs, it has resulted in the creation new useful jobs, such as manufacturing the actual technology to be used in a computer, and a computer specialist field that help to put the newly-made computers to use. Thus, if a job is able to be taken over by a machine that is incapable of independent thought, the job may be less suitable for a human being. While ATMs have replaced bank-tellers, we now have newly found jobs which focus on repairing, and manufacturing the ATM machines; it works like a two-edged sword.

RGB Components Color Images Encryption in FRT Ranges

RGB Components Color Images Encryption in FRT Ranges RGB Components Color Images Encryption in FRT Ranges Somayeh Komeylian Department of Tel-Communication Engineering, Islamic Azad University South Tehran Branch, Tehran, Iran Armin Mehrabian Department of Medical, Mashhad Medical Science University, Mashhad, Iran Saeed Komeylian Factory of graduated students, Department of Tel-Communication Engineering, Sharif University of Technology, Tehran, Iran Latest works are doing on date encryption/color Image in optic range as well as Digital ranges. In this research, color Images encryption has been done by RGB components in FRT ranges for any kind of encryption random phase codes. Moreover, one single-part encryption method has been performed for color twin images. Encrypted twin RGB images by their color map converted to indexed format. One Algorithm used for incorporating two images in order to encrypt in FRT domain. Outlined Algorithm of 15entering parameter involved generally that random phases could be considered as keys for encryption. Unsuitable selection of any keys during encryption will have negative results. Presence of many keys help in building system thats intensely safe against unpermitted accessibility it could be seen that encrypted images were completely safe against unpermitted time accessibility that has false fractional commands in all three channels. Keywords: RGB Components; Color Images; Encryption. By developing Multimedia network, connection and publication techniques, tendency to send and gain Digital Date, especially images, extended a lot. Protecting individual and hiding things for permitted users and ensuring accessibility for legal Data and security considered as the most important subject in connections and image storage. One of the certain ways for immunity is encryption different optic methods recommended well for Digital methods and encrypting images. That consisted of good recognition of (DRPE) Double random phase encryption [1-3]. This method statistically uses Double Random phase in entrance and Fourier phase for input image encryption into a stationary white noise. This method generalization conducted toward fractional Fourier domain and then considerable help has been done by authors and researchers [7, 8]. In addition, many remarkable works are doing on date encryption/color Image in optic range as well as Digital ranges. In the other related works for color Im ages encryption, RGB color Image RGB components in FRT ranges used for any kind of encryption random phase codes and FRT fractional commands as keys [6]. Moreover, one single-part encryption method has been performed for color twin images [5]. Encrypted twin RGB images by their color map converted to indexed format. One Algorithm used for incorporating two images in order to encrypt in FRT domain. Mentioned Method is Single-part and permitted processing in a simple direction [4]. A. Definition of FRT Conventionally, The nth order FRT fn(xn) Of a function f(x) is calculated using integral transform kernel given by follow equation [4]. (1) Where (2) Moreover, X and xn represent the coordinate systems for the input (zero order) domain and the output (nth order) fractional domain respectively. The FRT is linear and has the property that it is index additive: (3) Where a and b are different fractional orders of the FRT. It is possible to extend the definition of the FRT order beyond  ±2 (4) Where m is an integer. B. Concept of Colored Indexed Images Colored image in our context is represented as fn(x. y), where   x and y are spatial coordinates and n denotes the index of primary color components (n=0, 1, 2) f0(x. y), f1(x. y) and f2(x. y) correspond to RGB color components respectively. A colored image con be viewed as a stack as a stack of RGB components forming a m-n-3 array, with each pixel as a triplet corresponding to the values of the primary color components. On the other hand, an indexed image consists of a data matrix and a color map matrix. The color map matrix is an m-3 array of class double containing floating point values in the range [0, 1], where m is a function of the color system and it defines the number of colors it defines. Each row of the color map matrix specifies the red, green, and blue components of a single color. An indexed image uses direct mapping of the pixel intensity values to color map values. The color of each image pixel is determined by using the corresponding value of the data matrix as a pointer into color map. Unlike a colored image (Which is a 3-D matrix), an indexed image is a 2-D array, and simplifies the encryption as the color map is uniquely defined for a given color system. The same can be extracted from the color image and only a 2-D indexed image can be encrypted. Thus the process of encryption and decryption can be carried out in a single channel similar to the gray scale images, and the colored image can be retrieved after adding the color map to the decrypted indexed image [4]. A. Recommended Encryption Algorithm Colored image in our context is represented as follow equation: (5) Where, x and y are spatial coordinates and n denotes the index of primary color components (n=0, 1, 2) f0(x. y), f1(x. y) and f2(x. y) correspond to red, green, and blue color components respectively. Each of these components is segregated and the input RGB image p(x, y), to be encrypted, is converted into its indexed format pi (x, y), by extracting the color map and with each of these components are added. Each of these components encrypted independently using fractional Fourier encryption. The schematic of the proposed encryption technique is shown in Figure (1). The colored image to be encrypted is decomposed in red, green, and blue components and each of these components are combined with indexed image pi (x, y), and each component is multiplied with random phase functions ÃŽ ¦r1(x, y), ÃŽ ¦g1(x, y), and ÃŽ ¦b1(x, y). The random functions used above are statistically independent of each other. The FRT with different fractional orders along each spatial coordinate is performed for all the color components i. e (arx, ary) for red, (agx, agy) for green, and (abx, aby) for blue respectively. The transformed primary color images are then multiplied with three random phase functions ÃŽ ¦r2(u, Ï…), ÃŽ ¦g2(u, Ï…) and ÃŽ ¦b2(u, Ï…) in the fractional domain, where u and Ï… denote the coordinates in the respective fractional domain. Another FRT is performed subsequently on these images independently with different fractional orders along each spatial coordinates i.e. (brx, bry) for red (bgx, bgy) for green and (bbx, bby) for blue, in order to obtain the encrypted images for each of the three color components. In the final step, these three encrypted image are combined to get the colored encrypted image e(x, y). Figure 1: The color image encryption algorithm B. Recommended Decryption Algorithm The decryption process is described in Figure (2). The encrypted image is first decomposed into three primary color components. FRT of fractional orders (-brx, -bry), (-bgx, -bgy) and (-bbx, -bby) are calculated for the red, green, and blue color components, respectively and are subsequently multiplied with random phase functions ÃŽ ¦*r2(u, v), ÃŽ ¦*g2(u, v), and ÃŽ ¦*b2(u, v) in the fractional domain, where * denotes complex conjugate. In the next step, the FRTs of the fractional orders (-arx,-ary) for red, (-agx,-agy) for green- and (-abx,-aby) for blue-color images are calculated. Furthermore, indexed image pi (x, y) is segregated and finally these three components color images are combined to get the decrypted image. Figure 2: The color image decryption algorithm Figure (3a) is the main Image of globe and our main Image that will be encrypted. Figure (3b) is lena picture that would be index image incorporated with the main image. P(x,y) that has been shown in Figure (3b), and index image has been shown in Figure (3c) and finally encrypted image resulted as Figure (3d). Now, in encryption process, we must arrange it like this and see that encrypted image of globe will be as follows after separation. Figure 3: The Result of encryption In the previous part, observed results of encryption and decryption. Outlined Algorithm of 15entering parameter involved generally that random phases could be considered as keys for encryption. Unsuitable selection of any keys during encryption will have negative results. Presence of many keys help in building system thats intensely safe against unpermitted accessibility it could be seen that encrypted images were completely safe against unpermitted time accessibility that has false fractional commands in all three channels. References   P. Refregier, B. Javidi, (1995), Double random Fourier plane encoding, Opt. Lett. 20(1): 767-778. B. M. Hennelly, J. T. Sheridan, (2003), Image encryption and the fractional Fourier transform, Optik, 114(2): 6-15. B. M. Hennelly, J. T. Sheridan, (2003), Double random fractional Fourier plane encoding, Optik, 114(1): 251-262. M. Joshi, K. Singh, (2007), Color image encryption and decryption for twin images in fractional Fourier domain, Optics Communications, 281(1): 5713-20. M. Joshi, K. Singh, (2007), Color image encryption and decryption using fractional Fourier transform, Optics Communications, 279(1):35-42. Z. Liu, S. Li, (2007), Double image encryption based on iterative fractional Fourier transforms, Optics Communications, 275(1): 324-329. Y. Wang, S. Zhou, (2011), A Novel Image Encryption Algorithm Based on Fractional Fourier Transform, IEEE, 978(1): 4244. X. Feng, X. Tian, Sh. Xia, (2011), A Novel Image Encryption Algorithm Based On Fractional Fourier Transform and Magic Cube Rotation, IEEE, 978(1): 4244-9306

Review Of The Red Lantern :: essays research papers

There are some movies about lifestyles in China and then there is “Raise the Red Lantern.'; The film parallels “The Last Emperor'; in how a master controls his subjects within his domain. Out of all the Chinese movies that I have extensively viewed, this was the only one that actually, and effectively, captures the lush background of life during this time period.   Ã‚  Ã‚  Ã‚  Ã‚  The film entirely takes place on the grounds of a wealthy master whose only chore seems to be deciding which one of his four wives to sleep with on a given night. In viewing the movie, we are forced to feel sympathetic to the fourth mistress. She was the youngest among the other three who arrives at the estate after studying at the university. Cherished memories of her life before arriving there were ultimately destroyed. In one instance, the master burned the fourth mistress’s flute that her deceased father gave to her. The film evokes feelings of sorrow and disgust, but it manages to fill in humorous bits that alleviate the tense mood.   Ã‚  Ã‚  Ã‚  Ã‚  The film revolves around the master’s polygamist lifestyle and his utter dominance over his wives. When one mistress was good to him, he would decide to sleep with her that night. At the beginning of the film you get the notion that the forth mistress doesn’t want to sleep with the master, but that changes as the film goes on. Sleeping with the master that night meant the lanterns outside your room were lit up and, an added incentive, was being able to get a foot massage that night. The massage seemed to be the most rewarding part of being at the estate. The master’s decision of who to sleep with that night evoked jealousy between the “sisters.'; This increased the excitement of the movie and led to the main struggle between the fourth mistress and the three other women.   Ã‚  Ã‚  Ã‚  Ã‚   The fourth mistress’s anger and lack of control creates hostility in the household. Her behavior creates a downward spiral, which leads to the deaths of two important characters.

Contribution of Fishing Industry Towards Poverty Reduction in Zanzibar

THE UNIVERSIRY OF DODOMA COLLEGE OF HUMANITIES AND SOCIAL SCIENCES SCHOOL OF ECONOMICS AND BUSINESS STUDIES DEPERTMENT OF ECONOMICS AND STATISTICS RESEARCH – PROPOSAL. TOPIC: The contribution of fishing industry towards poverty reduction in Zanzibar. SUPERVISOR: CANDIDATE: MR. BONGOLE, A J MUSSA, HANIFU T/UDOM/2010/03536 Table of Contents THE UNIVERSIRY OF DODOMA1 COLLEGE OF HUMANITIES AND SOCIAL SCIENCES1 SCHOOL OF ECONOMICS AND BUSINESS STUDIES1DEPERTMENT OF ECONOMICS AND STATISTICS1 LIST OF ABBREVIATION3 CHAPTER ONE4 OVERVIEW OF THE STUDY4 1. 0 Introduction4 1. 1 Background Information to the problem4 1. 2Statement of the problem. 5 1. 3. Significant of the study5 1. 4 Scope of the study5 1. 5Objective of the research5 1. 5. 1General objectives. 5 1. 5. 2Specific objectives5 1. 6 . Hypothesis of the study6 CHAPTER TWO7 LITERATURE REVIEW. 7 2. 0. INTRODUCTION7 2. 1 Definition of fishing7 2. 1 Background of fishing Industry7 2. 2 Fishing in Zanzibar’s economy7 2. 3 POV ERTY REDUCTION8 . 4 Definition of poverty8 2. 4. 0: Growth and poverty8 CHAPTER THREE9 3. 0: METHODOLOGY9 3. 1 AREA OF THE STUDY10 3. 2 TARGETED POPULLATION10 3. 3 PURPOSE OF THE STUDY AND TYPE OF INVESTIGATION10 3. 4 DATA COLLECTION. 10 3. 5 SAMPLING DESIGN10 3. 6 QUESTIONNAIRE SURVEY11 3. 7 THE INTERVIEW SURVEY11 3. 8 DATA ANALYSIS11 3. 9 CONTRIBUTION OF THE STUDY11 MODEL OF THE STUDY11 BIBLIOGRAPHY12 QUESTIONNARES13 LIST OF ABBREVIATION BOT – Bank of Tanzania DD – Demand FDZ -Fisheries Department of ZanzibarGDP – Gross Domestic Product GOZ – Government of Zanzibar MOFEA – Ministry of Finance and Economic Affairs SMEs – Small and Medium Enterprises TZS – Tanzania Shillings UK – United Kingdom URT – United Republic of Tanzania USD – United States Dollars ZIPA – Zanzibar Investment Promotion Authority ZIP -Zanzibar Investment Policy ZNZ – Zanzibar ZPRP – Zanzibar Poverty Reduction Plan CHAPTER ONE OVERVIEW OF THE STUDY 1. 0 IntroductionThis chapter covers the contextual background of the problem stating clearly how the problem come about/historical development and what is being done so far on literature review , stating clearly the statement of the problem, general and specific research objectives, general and specific research questions. 1. 1 Background Information to the problem Zanzibar’s fishing is almost entirely artisanal and is conducted in the shallow waters along the coast. The entire fishing grounds are about 4,000 square kilometers for Unguja and 2,720 square kilometers for Pemba.Much of this area has coral reefs and a variety of flora and fauna making the region ideal for fishing. Indeed, there is an enormous potential for increased production of marine products, through offshore and deep-sea fishing including processing, for both domestic and export markets(ZIP). The Zanzibar Poverty Reduction Plan (ZPRP 2002) stipulates that growth in the agricultura l sector is crucial due to its pro-found positive impact on poverty reduction. Based on this back drop, once growth in agriculture is stimulated, most poor people in this sector will benefit culminating into poverty reduction.The fishing sub-sector has a relatively lower contribution in export compared to other exports such as cloves, manufactured goods and other exports. Statistics show that from 2000 to 2004 exports of fish amounted to USD 0. 53million accounting for 0. 7%of total exports amounting to USD 67. 5 million. (ZPRP 2002) However, the market potential is yet to be sufficiently exploited because of a fish catches , not withstanding the fact that Zanzibar is surrounded by sea. Generally, fishing activities in Zanzibar are concentrated on onshore.According to the Agricultural Policy(2000),the main reason for shallow sea fishing with low fish yield is lack of capital to purchase larger vessels to engage in deep sea fishing, indicating that fishing is not developed (some of f ishermen do not use fishing vessels but use rudimentary tools for catching fish such as spears sticks, knives, small nets and bare hands). Fish stocks include small pelagic, coral reef fish, lobsters, octopus and large pelagic etc The fishing territorial area is made of about 4,000sq. kms for Unguja or 59. 5% and 2,720sq. kms for Pemba accounting for 40. 5% of total.Statistics for fish catch indicate a fluctuating trend between 1992 and 1997,before attaining a steady increasing path from 1998 towards 2002. However the actual production is still low and does not contribute significantly in Zanzibar fish exports despite high potentiality. Distribution of fish catches by districts reveal that currently urban Unguja district is leading in fish production since 2001, outpacing North district which dominated before. Exports (export earnings) was the highest in 2003 because of the sea products such as sea shells and sea cucumber from the business people. The Zanzibar Poverty Reduction Plan (ZPRP Jan 2002)) 1. 2Statement of the problem. Zanzibar, having two islands namely Unguja and Pemba located in the Indian ocean have varieties of fish. The islands are accessible by sea, having two ports in Unguja and Pemba making it easier to export fish products, these factor facilities are important for developing fishing industry. According to Tanzania Reproductive and Child Health Survey(1999) about 35. 8% of under five children are stunted of which 12. 2% are severely stunted. For Pemba 46. 25% of under five children are stunted, while for ungula it is 27. 5% . The situation calls for a study to establish how the fishing industry can be improved (e. g. by identifying appropriate technology and reliable markets) to get rid of malnutrition, reduce poverty, increase export proceeds, increase tax revenue and increase employment opportunities. 1. 3. Significant of the study The finding of this research will encourage the concerned authorities to perform their duties that is by impr oving the fishing industry in order to reduce poverty and exercise their professions and responsibilities towards controlling the current problem which is poverty.Further more the study will collect information from different sources and use the findings to alert the authorities concerned about the fishing industry and how it will contribute towards reduction poverty. 1. 4 Scope of the study The study will take about 2 weeks in February and will cover Zanzibar as a case study which will be the inclusion of Unguja as it analyses the contribution of fishing industry towards poverty reduction in Zanzibar. 1. 5Objective of the research 1. 5. 1General objectives. To estimate the extent of fishing industry on poverty reduction in the study area 1. 5. Specific objectives The study will seek to achieve the following: To evaluate the potentiality of fishing in Zanzibar economy To identify problems and opportunities in fishing industry and its marketing in the study area To assess the applica bility of fishing industry towards the reduction of poverty in the study area 1. 6 . Hypothesis of the study The following will be tested in order to assess the validity of both overall and specific objectives. Does the fishing industry leads to the poverty reduction? That is: Null hypothesis (HO): Fisheries improvement is the determinant for poverty reduction.Alternative Hypothesis (Hi): fisheries improvement is not a determinant of poverty reduction. CHAPTER TWO LITERATURE REVIEW. 2. 0. INTRODUCTION This study comprises literature review about the contribution of fishing industry towards the poverty reduction in Zanzibar. These reviews include books, journals, articles and details from the Ministry of Agriculture and Fisheries Department. This chapter is divided into two parts. The first part deals with Fishing Industry and the second part is a review in Poverty Reduction. 2. 1 Definition of fishingFrom the encyclopedia (Britanica) ; – Fishing involves the recovery of foods and other valuable resources from bodies of water. Fishing involves the extraction of all marine products. – Fishery; is harvesting of as a commercial enterprise or the location or season of commercial fishing. 2. 1 Background of fishing Industry (FDZ) Government of Zanzibar’s involvement in fishing activities started many years ago but because of abundant resources, few fishers and primitive gear, fisheries activities were not considered important.Before 1964 revolution, there was a private fishing corporation under management of the Greeks, which was charged with supervision of all fishing activities in Zanzibar. After the 1964 Revolution, the Government of Zanzibar nationalized the corporation as established it as public enterprise charged with the responsibility of monitoring fishing activities and improving working conditions of the fisher folk. In 1974,the Revolutionary Government of Zanzibar formed the Department of Fisheries, under the Ministry of Agriculture, Livestock and Environment.Besides other functions, and key responsibility of the department was directed to supervise and modernize fishery activities. In order to modernize fishing, the department of Fisheries established several centres for coordinating, simplifying and promoting fishing activities. 2. 2 Fishing in Zanzibar’s economy Unguja and Pemba are surrounded by rich marine resources, the people of Zanzibar utilize marine products for subsistence and as a source of income, with fish being among the most important resources and socio-economic activities of the people in Zanzibar economy.Fishing has been conducted in the islands since the dawn of humanity and still continues to be an important coastal activity. Fishing provides employment for men and women and almost all age groups. Fishing activity employs an average of 25% of the population as artisanal fishers and account for an average of 4. 5% of GDP. According to the recent data provided by Ministry of Agricultur e, Livestock and Environment( Department of Fisheries and Marine Resources – Zanzibar),there has been gradual decrease in the GDP accounted from fishing sector.In 2004 GDP for fish had increased to 5% and it kept on increasing in 2005 reaching 5. 9% but from there it went on decreasing in the year 2006 reaching 4. 9%. So in my study i will try to look for the reason of decreasing in this fishing industry and try to look at which ways the government suppose to do to improve it and help the people of Zanzibar that is reduce the poverty. 2. 3 POVERTY REDUCTION Before getting to the concept of Poverty Reduction, the meaning of Poverty should be understood. 2. 4 Definition of poverty According to the World’s encyclopaedia 9:652:3aPoverty is the condition that is said to exist when people lack the means to satisfy their basic needs which are necessary for survival. According to Gerald M. Meir and James E. Rauch in the book Leading Issues in Economic Development (seventh edit ion) ; Poverty is concerned with the absolute standard of living of a part of the society. According to Michael Todaro and Stephen Smith in their book Economic Development ; Poverty is the number of people who are unable to command sufficient resources to satisfy basic needs. it’s a total number living below a specified minimum level of real income – an international poverty line.Most current projections call for the number of persons living in poverty to rise over the current decade but this outcome depends on two factors; – the rate of economic growth – the level of resources devoted to poverty programs and the quality of those programs. 2. 4. 0: Growth and poverty Rapid growth is bad for the poor because they would be bypassed by the structural changes of modern growth. I will try to look how the public expenditures required for the reduction of poverty would entail the reduction in the rate of growth.The poor tend to spend additional income on improve d nutrition, education for children, improvements in housing conditions and other expenditures that especially at poverty levels represent investments rather than consumption. Reasons why policies focused towards reducing poverty levels need not to lead in slower rate of growth ; i. widespread poverty creates conditions in which the poor have no access to credit, are unable to finance their children’s education and the absence of physical or monetary investment opportunities. ii.The low incomes and the low level of living for the poor which are manifested in poor health, nutrition and education can lower their economic productivity and lead to the slower growing economy. iii. Raising the income levels of the poor will stimulate an overall increase in the demand for locally produced necessity products like food and clothing whereas the rich tend to spend on luxury goods. iv. A reduction of mass poverty can stimulate healthy economic expansion by acting as a powerful material a nd psychological incentive to widespread public participation in the development process. CHAPTER THREE . 0: METHODOLOGY. The methodology that will be applied in my study has been chosen in order to acquire information and deduce conclusions about the contribution of fishing industry towards poverty reduction and the alternative measures which should be taken in order to make sure that they adapt to this problem. 3. 1 AREA OF THE STUDY The study will be conducted at mkokotoni fishing site in Zanzibar and the Department of fisheries, where fishermen and officers of fisheries were involved. 3. 2 TARGETED POPULLATION The targeted populations are officials from the Department of Fisheries and the fishermen.As it is not easy to deal with each individual in the department and all the fishermen available in Zanzibar, a research used sampling method that is simple random to get actual respondents and in reducing sampling errors. A sample of 10 to 20 fishermen will be drawn from the populati on. 3. 3 PURPOSE OF THE STUDY AND TYPE OF INVESTIGATION The main purpose of this study Is to obtain an insight into the current contribution of fishing industry towards poverty reduction in Zanzibar. For the above reason, this research will take an exploratory approach.According Sekaran (2002:123) an exploratory study is undertaken when not much is known about the situation at hand, or when no information is available on how similar problems or research issues have been solved in the past. The aim will be to gain familiarity with the issues, and to gain a deeper understanding about the topic and to come out with the suggestive measures which should be taken to adapt to this problem of fishing industry. 3. 4 DATA COLLECTION. For the purpose of this research, and in order to achieve the objectives data will be collected and will use both primary and secondary data.The secondary data will contribute toward the formation of background information, needed by both the researcher in order to build constructively the project and the reader to comprehend more thoroughly the survey outcome. Primary data will be collected in two ways. Firstly, a questionnaire survey will be conducted with researcher visiting the area. Secondly, interviews will be also carried out with I will go to the fishermen and asking them about how there work has contributed towards reduction of poverty. 3. 5 SAMPLING DESIGN Ideally I wanted to study the entire population of fishermen.However, it will be impossible and unfeasible to do this and therefore I must settle for a sample. According to Kothari C. R, sample is a portion of elements taken from a population, which is considered to be representative of the population. In order to collect primary data the questionnaires survey technique will be used. For the purpose of this study I will use both simple random probability sampling and purposive random sampling. Under simple random sampling each of the fisherman found in the area visited will be a ble to provide with information on how he/she contribute to reduction of poverty.Also under purposive random sampling I will be responsible of setting some criteria on whom to interview. 3. 6 QUESTIONNAIRE SURVEY In order to achieve my goal of this study and get relevant information about this problem I will use both closed and open ended questions. Under the closed ended questions I will narrow the field inquiry and will choose among the fixed responses. This will enable me to analyze my data easier since the responses will be easier to compare. Also the open ended questions will enable me to get new ideas and varieties of information about the problem. 3. 7 THE INTERVIEW SURVEYThe technique of personal interviewing is undertaken in order to reach the objectives since it is the most versatile and productive method of communication, enabled spontaneity, and also provided with: â€Å"The skill of guiding the discussion back to the topic outlined when discussions are unfruitful thoug h it has the disadvantages of being very costly time consuming and can introduce bias through desires of the respondent to please the interviewer. 3. 8 DATA ANALYSIS After collecting the data from the field I will use Microsoft excel and Statistical Packages for Social Sciences (SPSS).These methods will enable me to draw a valid conclusion of what I will find in the field in relation to the objectives I have put forward. 3. 9 CONTRIBUTION OF THE STUDY As it is the purposes of this study that it helps to investigate the contribution of fishing industry towards poverty reduction. When I complete this research I will add an important value on the academic part. Also the purpose of this study is to enable me understand on how I can conduct research on different cases. MODEL OF THE STUDY In my study as the qualitative research there is the need of using a model to est the result of the research, here the multiple regression model will be used for the test of my research. The model of my study will be as follows: Y =? 0 + ? 1X1 + ? 2X2 + ? 3X3 + ? 4X4 +  µ Where; Y – stands for Income X1 – stands for education level X2 – stands for technological level X3 – stands for age of the fisherman X4 – stands for financial assistance X5 – stands for family size  µ – stands for Error term as Y stands for dependent variable that is it depends on the changes of its explanatory variables. Independent variables can be explained as follows;Education level- that is if the education level of fisheries is high we expect to have more income and if its low expect low income. Technological level – that is the use of more advanced technology leads to increase in income. Age- as how ages leads to increase in income, that as ages goes up or down leads to increase in income. Financial assistance- that is how the government financially assists this sector as assisted more we expect for more income. Family size – Family size of a respondent was one variable (continuous variable) proposed to influence participation decision.The more number of family members an individual had the more probable to participate in fishing. This is because he will have a labor source. BIBLIOGRAPHY Gerald M. Meier,et al, â€Å" Leading issues in Economic Development† â€Å"seventh edition† Humphrey P. B. et al,. Zanzibar: The challenges of globalization and Poverty reduction Jiddawi N, M. (1997) : Fisheries stock Assessment in the Traditional Fisheries sector. Kothari C. (2004) â€Å"Research Methodology: methods and techniques† New Age international (P) limited, New Delhi. Michael P. T,et al, â€Å"Economic Development† Mkenda, A. 2001 â€Å"Fishery Resources and welfare in Rural Zanzibar†World’s encyclopaedia (Britanica) QUESTIONNARES 1. What is your name?†¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦ Sex; male ( ) female( ) AGE: 18 – 25| | 26 – 37| | 37 – 57| | Above 57| | MARITAL STATUS: Single| | Married| | Divorced| | Widowed| | Others| | 2. What is your level of education? | Level of education| Tick (v)| A| Primary level | | B| Secondary level| | C| Advanced level| | D| University level| | E| None| | 3. How many children do u have?†¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦. Are they participate with you in fishing. Yes ( ) No ( ) 4.For how long have you been working in fishing?†¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦ †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦ †¦. 5. How do you see the development of fishing? Put ( v ) where applicable Increasing/developing? ( ) wasting? ( ) Or you’re not sure? ( ) Specify your answer†¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦. †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦.. 6. Are you fishing only here or you are shifting? If shifting, why?†¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚ ¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦.. †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦.. . Which tools are you using for fishing? i). Advanced tools ( ) ii). Traditional tools ( ) if others specify†¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦ 8. Are you the owner of the tools you are using? Yes ( ) / No ( ) 9. Is there any other activities you are doing in spite of fishing? Yes( ) / No ( ) If yes tick (v) where applicable i. Farming| | ii. Hunting| | iii. Livestock keeping| | iv. Others| | If others, specify†¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦. 10. Do you have the market for your fishes? Yes( ) / No ( ) Tick (v) where applicable Internationally| |Nationally | | 11. How much money do you get for single fishing? †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦. 12. Do you thing this work of fishing is reducing the hardship of life? Yes ( ) / No ( ) How, †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦.. †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦. 13. Why do you think fishing has been decreasing in these recently years? †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦ †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦. †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦ †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦. THE UNIVERSITY OF DODOMA PROPOSAL The contribution of fishing industry towards poverty reduction in Zanzibar. BY Mussa, Hanifu Contribution of Fishing Industry Towards Poverty Reduction in Zanzibar THE UNIVERSIRY OF DODOMA COLLEGE OF HUMANITIES AND SOCIAL SCIENCES SCHOOL OF ECONOMICS AND BUSINESS STUDIES DEPERTMENT OF ECONOMICS AND STATISTICS RESEARCH – PROPOSAL. TOPIC: The contribution of fishing industry towards poverty reduction in Zanzibar. SUPERVISOR: CANDIDATE: MR. BONGOLE, A J MUSSA, HANIFU T/UDOM/2010/03536 Table of Contents THE UNIVERSIRY OF DODOMA1 COLLEGE OF HUMANITIES AND SOCIAL SCIENCES1 SCHOOL OF ECONOMICS AND BUSINESS STUDIES1DEPERTMENT OF ECONOMICS AND STATISTICS1 LIST OF ABBREVIATION3 CHAPTER ONE4 OVERVIEW OF THE STUDY4 1. 0 Introduction4 1. 1 Background Information to the problem4 1. 2Statement of the problem. 5 1. 3. Significant of the study5 1. 4 Scope of the study5 1. 5Objective of the research5 1. 5. 1General objectives. 5 1. 5. 2Specific objectives5 1. 6 . Hypothesis of the study6 CHAPTER TWO7 LITERATURE REVIEW. 7 2. 0. INTRODUCTION7 2. 1 Definition of fishing7 2. 1 Background of fishing Industry7 2. 2 Fishing in Zanzibar’s economy7 2. 3 POV ERTY REDUCTION8 . 4 Definition of poverty8 2. 4. 0: Growth and poverty8 CHAPTER THREE9 3. 0: METHODOLOGY9 3. 1 AREA OF THE STUDY10 3. 2 TARGETED POPULLATION10 3. 3 PURPOSE OF THE STUDY AND TYPE OF INVESTIGATION10 3. 4 DATA COLLECTION. 10 3. 5 SAMPLING DESIGN10 3. 6 QUESTIONNAIRE SURVEY11 3. 7 THE INTERVIEW SURVEY11 3. 8 DATA ANALYSIS11 3. 9 CONTRIBUTION OF THE STUDY11 MODEL OF THE STUDY11 BIBLIOGRAPHY12 QUESTIONNARES13 LIST OF ABBREVIATION BOT – Bank of Tanzania DD – Demand FDZ -Fisheries Department of ZanzibarGDP – Gross Domestic Product GOZ – Government of Zanzibar MOFEA – Ministry of Finance and Economic Affairs SMEs – Small and Medium Enterprises TZS – Tanzania Shillings UK – United Kingdom URT – United Republic of Tanzania USD – United States Dollars ZIPA – Zanzibar Investment Promotion Authority ZIP -Zanzibar Investment Policy ZNZ – Zanzibar ZPRP – Zanzibar Poverty Reduction Plan CHAPTER ONE OVERVIEW OF THE STUDY 1. 0 IntroductionThis chapter covers the contextual background of the problem stating clearly how the problem come about/historical development and what is being done so far on literature review , stating clearly the statement of the problem, general and specific research objectives, general and specific research questions. 1. 1 Background Information to the problem Zanzibar’s fishing is almost entirely artisanal and is conducted in the shallow waters along the coast. The entire fishing grounds are about 4,000 square kilometers for Unguja and 2,720 square kilometers for Pemba.Much of this area has coral reefs and a variety of flora and fauna making the region ideal for fishing. Indeed, there is an enormous potential for increased production of marine products, through offshore and deep-sea fishing including processing, for both domestic and export markets(ZIP). The Zanzibar Poverty Reduction Plan (ZPRP 2002) stipulates that growth in the agricultura l sector is crucial due to its pro-found positive impact on poverty reduction. Based on this back drop, once growth in agriculture is stimulated, most poor people in this sector will benefit culminating into poverty reduction.The fishing sub-sector has a relatively lower contribution in export compared to other exports such as cloves, manufactured goods and other exports. Statistics show that from 2000 to 2004 exports of fish amounted to USD 0. 53million accounting for 0. 7%of total exports amounting to USD 67. 5 million. (ZPRP 2002) However, the market potential is yet to be sufficiently exploited because of a fish catches , not withstanding the fact that Zanzibar is surrounded by sea. Generally, fishing activities in Zanzibar are concentrated on onshore.According to the Agricultural Policy(2000),the main reason for shallow sea fishing with low fish yield is lack of capital to purchase larger vessels to engage in deep sea fishing, indicating that fishing is not developed (some of f ishermen do not use fishing vessels but use rudimentary tools for catching fish such as spears sticks, knives, small nets and bare hands). Fish stocks include small pelagic, coral reef fish, lobsters, octopus and large pelagic etc The fishing territorial area is made of about 4,000sq. kms for Unguja or 59. 5% and 2,720sq. kms for Pemba accounting for 40. 5% of total.Statistics for fish catch indicate a fluctuating trend between 1992 and 1997,before attaining a steady increasing path from 1998 towards 2002. However the actual production is still low and does not contribute significantly in Zanzibar fish exports despite high potentiality. Distribution of fish catches by districts reveal that currently urban Unguja district is leading in fish production since 2001, outpacing North district which dominated before. Exports (export earnings) was the highest in 2003 because of the sea products such as sea shells and sea cucumber from the business people. The Zanzibar Poverty Reduction Plan (ZPRP Jan 2002)) 1. 2Statement of the problem. Zanzibar, having two islands namely Unguja and Pemba located in the Indian ocean have varieties of fish. The islands are accessible by sea, having two ports in Unguja and Pemba making it easier to export fish products, these factor facilities are important for developing fishing industry. According to Tanzania Reproductive and Child Health Survey(1999) about 35. 8% of under five children are stunted of which 12. 2% are severely stunted. For Pemba 46. 25% of under five children are stunted, while for ungula it is 27. 5% . The situation calls for a study to establish how the fishing industry can be improved (e. g. by identifying appropriate technology and reliable markets) to get rid of malnutrition, reduce poverty, increase export proceeds, increase tax revenue and increase employment opportunities. 1. 3. Significant of the study The finding of this research will encourage the concerned authorities to perform their duties that is by impr oving the fishing industry in order to reduce poverty and exercise their professions and responsibilities towards controlling the current problem which is poverty.Further more the study will collect information from different sources and use the findings to alert the authorities concerned about the fishing industry and how it will contribute towards reduction poverty. 1. 4 Scope of the study The study will take about 2 weeks in February and will cover Zanzibar as a case study which will be the inclusion of Unguja as it analyses the contribution of fishing industry towards poverty reduction in Zanzibar. 1. 5Objective of the research 1. 5. 1General objectives. To estimate the extent of fishing industry on poverty reduction in the study area 1. 5. Specific objectives The study will seek to achieve the following: To evaluate the potentiality of fishing in Zanzibar economy To identify problems and opportunities in fishing industry and its marketing in the study area To assess the applica bility of fishing industry towards the reduction of poverty in the study area 1. 6 . Hypothesis of the study The following will be tested in order to assess the validity of both overall and specific objectives. Does the fishing industry leads to the poverty reduction? That is: Null hypothesis (HO): Fisheries improvement is the determinant for poverty reduction.Alternative Hypothesis (Hi): fisheries improvement is not a determinant of poverty reduction. CHAPTER TWO LITERATURE REVIEW. 2. 0. INTRODUCTION This study comprises literature review about the contribution of fishing industry towards the poverty reduction in Zanzibar. These reviews include books, journals, articles and details from the Ministry of Agriculture and Fisheries Department. This chapter is divided into two parts. The first part deals with Fishing Industry and the second part is a review in Poverty Reduction. 2. 1 Definition of fishingFrom the encyclopedia (Britanica) ; – Fishing involves the recovery of foods and other valuable resources from bodies of water. Fishing involves the extraction of all marine products. – Fishery; is harvesting of as a commercial enterprise or the location or season of commercial fishing. 2. 1 Background of fishing Industry (FDZ) Government of Zanzibar’s involvement in fishing activities started many years ago but because of abundant resources, few fishers and primitive gear, fisheries activities were not considered important.Before 1964 revolution, there was a private fishing corporation under management of the Greeks, which was charged with supervision of all fishing activities in Zanzibar. After the 1964 Revolution, the Government of Zanzibar nationalized the corporation as established it as public enterprise charged with the responsibility of monitoring fishing activities and improving working conditions of the fisher folk. In 1974,the Revolutionary Government of Zanzibar formed the Department of Fisheries, under the Ministry of Agriculture, Livestock and Environment.Besides other functions, and key responsibility of the department was directed to supervise and modernize fishery activities. In order to modernize fishing, the department of Fisheries established several centres for coordinating, simplifying and promoting fishing activities. 2. 2 Fishing in Zanzibar’s economy Unguja and Pemba are surrounded by rich marine resources, the people of Zanzibar utilize marine products for subsistence and as a source of income, with fish being among the most important resources and socio-economic activities of the people in Zanzibar economy.Fishing has been conducted in the islands since the dawn of humanity and still continues to be an important coastal activity. Fishing provides employment for men and women and almost all age groups. Fishing activity employs an average of 25% of the population as artisanal fishers and account for an average of 4. 5% of GDP. According to the recent data provided by Ministry of Agricultur e, Livestock and Environment( Department of Fisheries and Marine Resources – Zanzibar),there has been gradual decrease in the GDP accounted from fishing sector.In 2004 GDP for fish had increased to 5% and it kept on increasing in 2005 reaching 5. 9% but from there it went on decreasing in the year 2006 reaching 4. 9%. So in my study i will try to look for the reason of decreasing in this fishing industry and try to look at which ways the government suppose to do to improve it and help the people of Zanzibar that is reduce the poverty. 2. 3 POVERTY REDUCTION Before getting to the concept of Poverty Reduction, the meaning of Poverty should be understood. 2. 4 Definition of poverty According to the World’s encyclopaedia 9:652:3aPoverty is the condition that is said to exist when people lack the means to satisfy their basic needs which are necessary for survival. According to Gerald M. Meir and James E. Rauch in the book Leading Issues in Economic Development (seventh edit ion) ; Poverty is concerned with the absolute standard of living of a part of the society. According to Michael Todaro and Stephen Smith in their book Economic Development ; Poverty is the number of people who are unable to command sufficient resources to satisfy basic needs. it’s a total number living below a specified minimum level of real income – an international poverty line.Most current projections call for the number of persons living in poverty to rise over the current decade but this outcome depends on two factors; – the rate of economic growth – the level of resources devoted to poverty programs and the quality of those programs. 2. 4. 0: Growth and poverty Rapid growth is bad for the poor because they would be bypassed by the structural changes of modern growth. I will try to look how the public expenditures required for the reduction of poverty would entail the reduction in the rate of growth.The poor tend to spend additional income on improve d nutrition, education for children, improvements in housing conditions and other expenditures that especially at poverty levels represent investments rather than consumption. Reasons why policies focused towards reducing poverty levels need not to lead in slower rate of growth ; i. widespread poverty creates conditions in which the poor have no access to credit, are unable to finance their children’s education and the absence of physical or monetary investment opportunities. ii.The low incomes and the low level of living for the poor which are manifested in poor health, nutrition and education can lower their economic productivity and lead to the slower growing economy. iii. Raising the income levels of the poor will stimulate an overall increase in the demand for locally produced necessity products like food and clothing whereas the rich tend to spend on luxury goods. iv. A reduction of mass poverty can stimulate healthy economic expansion by acting as a powerful material a nd psychological incentive to widespread public participation in the development process. CHAPTER THREE . 0: METHODOLOGY. The methodology that will be applied in my study has been chosen in order to acquire information and deduce conclusions about the contribution of fishing industry towards poverty reduction and the alternative measures which should be taken in order to make sure that they adapt to this problem. 3. 1 AREA OF THE STUDY The study will be conducted at mkokotoni fishing site in Zanzibar and the Department of fisheries, where fishermen and officers of fisheries were involved. 3. 2 TARGETED POPULLATION The targeted populations are officials from the Department of Fisheries and the fishermen.As it is not easy to deal with each individual in the department and all the fishermen available in Zanzibar, a research used sampling method that is simple random to get actual respondents and in reducing sampling errors. A sample of 10 to 20 fishermen will be drawn from the populati on. 3. 3 PURPOSE OF THE STUDY AND TYPE OF INVESTIGATION The main purpose of this study Is to obtain an insight into the current contribution of fishing industry towards poverty reduction in Zanzibar. For the above reason, this research will take an exploratory approach.According Sekaran (2002:123) an exploratory study is undertaken when not much is known about the situation at hand, or when no information is available on how similar problems or research issues have been solved in the past. The aim will be to gain familiarity with the issues, and to gain a deeper understanding about the topic and to come out with the suggestive measures which should be taken to adapt to this problem of fishing industry. 3. 4 DATA COLLECTION. For the purpose of this research, and in order to achieve the objectives data will be collected and will use both primary and secondary data.The secondary data will contribute toward the formation of background information, needed by both the researcher in order to build constructively the project and the reader to comprehend more thoroughly the survey outcome. Primary data will be collected in two ways. Firstly, a questionnaire survey will be conducted with researcher visiting the area. Secondly, interviews will be also carried out with I will go to the fishermen and asking them about how there work has contributed towards reduction of poverty. 3. 5 SAMPLING DESIGN Ideally I wanted to study the entire population of fishermen.However, it will be impossible and unfeasible to do this and therefore I must settle for a sample. According to Kothari C. R, sample is a portion of elements taken from a population, which is considered to be representative of the population. In order to collect primary data the questionnaires survey technique will be used. For the purpose of this study I will use both simple random probability sampling and purposive random sampling. Under simple random sampling each of the fisherman found in the area visited will be a ble to provide with information on how he/she contribute to reduction of poverty.Also under purposive random sampling I will be responsible of setting some criteria on whom to interview. 3. 6 QUESTIONNAIRE SURVEY In order to achieve my goal of this study and get relevant information about this problem I will use both closed and open ended questions. Under the closed ended questions I will narrow the field inquiry and will choose among the fixed responses. This will enable me to analyze my data easier since the responses will be easier to compare. Also the open ended questions will enable me to get new ideas and varieties of information about the problem. 3. 7 THE INTERVIEW SURVEYThe technique of personal interviewing is undertaken in order to reach the objectives since it is the most versatile and productive method of communication, enabled spontaneity, and also provided with: â€Å"The skill of guiding the discussion back to the topic outlined when discussions are unfruitful thoug h it has the disadvantages of being very costly time consuming and can introduce bias through desires of the respondent to please the interviewer. 3. 8 DATA ANALYSIS After collecting the data from the field I will use Microsoft excel and Statistical Packages for Social Sciences (SPSS).These methods will enable me to draw a valid conclusion of what I will find in the field in relation to the objectives I have put forward. 3. 9 CONTRIBUTION OF THE STUDY As it is the purposes of this study that it helps to investigate the contribution of fishing industry towards poverty reduction. When I complete this research I will add an important value on the academic part. Also the purpose of this study is to enable me understand on how I can conduct research on different cases. MODEL OF THE STUDY In my study as the qualitative research there is the need of using a model to est the result of the research, here the multiple regression model will be used for the test of my research. The model of my study will be as follows: Y =? 0 + ? 1X1 + ? 2X2 + ? 3X3 + ? 4X4 +  µ Where; Y – stands for Income X1 – stands for education level X2 – stands for technological level X3 – stands for age of the fisherman X4 – stands for financial assistance X5 – stands for family size  µ – stands for Error term as Y stands for dependent variable that is it depends on the changes of its explanatory variables. Independent variables can be explained as follows;Education level- that is if the education level of fisheries is high we expect to have more income and if its low expect low income. Technological level – that is the use of more advanced technology leads to increase in income. Age- as how ages leads to increase in income, that as ages goes up or down leads to increase in income. Financial assistance- that is how the government financially assists this sector as assisted more we expect for more income. Family size – Family size of a respondent was one variable (continuous variable) proposed to influence participation decision.The more number of family members an individual had the more probable to participate in fishing. This is because he will have a labor source. BIBLIOGRAPHY Gerald M. Meier,et al, â€Å" Leading issues in Economic Development† â€Å"seventh edition† Humphrey P. B. et al,. Zanzibar: The challenges of globalization and Poverty reduction Jiddawi N, M. (1997) : Fisheries stock Assessment in the Traditional Fisheries sector. Kothari C. (2004) â€Å"Research Methodology: methods and techniques† New Age international (P) limited, New Delhi. Michael P. T,et al, â€Å"Economic Development† Mkenda, A. 2001 â€Å"Fishery Resources and welfare in Rural Zanzibar†World’s encyclopaedia (Britanica) QUESTIONNARES 1. What is your name?†¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦ Sex; male ( ) female( ) AGE: 18 – 25| | 26 – 37| | 37 – 57| | Above 57| | MARITAL STATUS: Single| | Married| | Divorced| | Widowed| | Others| | 2. What is your level of education? | Level of education| Tick (v)| A| Primary level | | B| Secondary level| | C| Advanced level| | D| University level| | E| None| | 3. How many children do u have?†¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦. Are they participate with you in fishing. Yes ( ) No ( ) 4.For how long have you been working in fishing?†¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦ †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦ †¦. 5. How do you see the development of fishing? Put ( v ) where applicable Increasing/developing? ( ) wasting? ( ) Or you’re not sure? ( ) Specify your answer†¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦. †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦.. 6. Are you fishing only here or you are shifting? If shifting, why?†¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚ ¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦.. †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦.. . Which tools are you using for fishing? i). Advanced tools ( ) ii). Traditional tools ( ) if others specify†¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦ 8. Are you the owner of the tools you are using? Yes ( ) / No ( ) 9. Is there any other activities you are doing in spite of fishing? Yes( ) / No ( ) If yes tick (v) where applicable i. Farming| | ii. Hunting| | iii. Livestock keeping| | iv. Others| | If others, specify†¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦. 10. Do you have the market for your fishes? Yes( ) / No ( ) Tick (v) where applicable Internationally| |Nationally | | 11. How much money do you get for single fishing? †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦. 12. Do you thing this work of fishing is reducing the hardship of life? Yes ( ) / No ( ) How, †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦.. †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦. 13. Why do you think fishing has been decreasing in these recently years? †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦ †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦. †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦ †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦. THE UNIVERSITY OF DODOMA PROPOSAL The contribution of fishing industry towards poverty reduction in Zanzibar. BY Mussa, Hanifu

Impact of Corporate Governance on Firm Performance

Impact of Corporate Governance on Firm Performance—an Empirical investigation from the Insurance Industry of Pakistan Hafiz Muhammad Raheel Arif* [email  protected] com 00923216190575 *COMSATS Institute of Information Technology and Science Lahore, Pakistan Abstract The study is devoted to check the impact of corporate governance (CG) on the firm performance (FP) of the insurance industry of Pakistan. Four measures have been used in the paper to check the firm performance being affected by the corporate governance. These measures are Return on Assets (ROA), Return on Equity (ROE), and Market to Book ratio and Price Earnings ratio.Data of 24 insurance companies is taken from websites of the companies and Karachi Stock Exchange website for the years 2007-2011 making up 107 observations excluding the missing observations. Pooled Ordinary Least Square (POLS) regression technique is used to regress the data. Findings of this study conclude that Institutional Shareholding ratio, B oard Size and Independent Directors’ ratio affect firm performance in the positive way whereas, CEO duality, Firm size, and Leverage have negative impact on firm performance overall when firm performance measured through four different measures.In future, the study may be extended to more corporate governance variables and increased sample size so that more generalized results may be achieved. Key words: Corporate Governance, Firm Performance, Insurance Industry, Pakistan. Introduction C orporate governance has now gained very much importance in the corporate world. Almost in all the countries around the globe corporate governance has become mandatory and is regulated by the concerning bodies. Like in Pakistan, this is mandatory for the corporations to comply with the best practices according to the Code of Corporate Governance [*].Various studies have attempted to probe into the relationship of corporate governance with the firm performance in the corporate world across vari ous countries. The study strives to investigate the impact of corporate governance on firm performance in the Insurance industry of Pakistan. The study basically extends the findings of Naser Najjar (2012), in his study; Naser * Code of corporate governance is included in the Regulation No. 37 for the listing regulations of Karachi Stock Exchange to ensure the best practices of corporate governance in Pakistan.Najjar (2012) investigated the relationship of corporate governance with firm performance by empirically examining this relationship of CG and firm performance in the insurance industry of the Behrain. In his study Naser Najjar (2012) used only Return on Equity as a measure of the financial performance. This study employs more financial performance measuring variables like Return on Assets, Market to Book ratios, and Price Earnings ratios by controlling firm size and the leverage ratio.Naser Najjar (2012) found a positive association between firm size and the performance of th e insurance companies suggesting that as the size increases the assets are more with the firms in the form of insurance policies and firms efficiently manage things to an ultimate gain. In their study Ming-Cheng Wu, Hsin-Chiang Lin, I-Cheng Lin, and Chun-Feng Lai found the positive relationship of firm size with the performance when measured by Return on Assets.Board size showed a negative relation in the past studies as in the study of Ming-Cheng Wu, Hsin-Chiang Lin, I-Cheng Lin, and Chun-Feng Lai; they found that board size is negatively associated with the firm performance due to the reason of board’s composition of inside as well as outside directors, and inside directors would have relatively high level of information regarding company’s internal affairs than outside directors and inside directors would work in their own interest and may confiscate the rights of shareholders and as the number of inside directors increases it makes the performance down.While anothe r study, Bacon (1973) gave a different opinion that larger board size positively affects the performance justifying in a way that larger board usually comes with a diversified background and qualifications which generates different viewpoints and hence increases quality of managerial decisions. One another very important way to control corporate bodies by reducing agency issues is to separate the CEO from Chairman (William et al. 2003).If these two characters are performed by a single individual, is known as CEO Duality. This situation if exists, reduces firm performance as there would be no one to â€Å"watch the watchers† (Zubaidah 2009). Independency of directors yet another variable to reduce confiscation of shareholders’ rights as independent directors would work in the best interest of the shareholders. The more the independent directors in the board, higher will be the performance of the firm (Zubaidah 2009).Upcoming sections are composed as; Next section review s the literature regarding the variables of corporate governance and performance measure. Then there comes the methodology section followed by the findings and results with conclusion at the end. Review of Literature Enormous studies empirically investigated the relationship between corporate governance and firm performance regarding various types of industries and across the world. Insurance industry is one of the financial sectors of any economy and it continuously gaining importance in Pakistan.Likewise, the issues of governing corporate bodies are raised during practices, the reason the study intends to check impact of corporate governance on the firm performance in the insurance industry of Pakistan. A number of studies used ROE and ROA as a measure of performance while checking for the impact of corporate governance on these variables. Naser Najjar (2012) found that there does not exist any significant association between CEO Duality as a measure of corporate governance and Re turn on Equity (ROE) as a performance measure.Masood Fooladi Chaghadari (2011) found negative relation between CEO Duality and firm performance which tells about the fact that if a single person acts as CEO and Chairman of the board it will reduce the performance of a firm. The study of Sanjai Bhagat & Brian Bolton (2007) also suggests the same results; the separation of CEO and Chairman of the board is positively and significantly associated to the firm performance. Anthony Kyereboah-Coleman (International Conference on Corporate Governance in Emerging Markets) in his study found that CEO duality has negatively relationship with the firm performance.Sanjai Bhagat & Brian Bolton (2007) found very interestingly the negative relationship of board independence with operating performance and made it relevant that with respect to the board independence which received corporate governance listing requirement from NYSE and NASDAQ. Masood Fooladi Chaghadari (2011) found negative relation of leverage with ROA and positive relation of the same variable with ROE. Anthony Kyereboah-Coleman (International Conference on Corporate Governance in Emerging Markets) also found negative relation of leverage with Return on Assets. Methodology I. Sample DataThe study initially undertook data of randomly selected 27 insurance companies of Pakistan from 2007-2011 making up 135 observations out of which 3 companies showed incomplete information due to which they were excluded from the study and 13 observations were missing in the data. The study then includes 107 observations. Data is collected from Karachi Stock Exchange (KSE) and websites of insurance companies. Current study has used Pooled Ordinary Least Square (POLS) regression method to regress the data collected to fulfill the objective of measuring impact of corporate governance on firm performance. II.Models In order to measure the firm performance the current study uses 4 different measures viz. Return on Assets (ROA), Retur n on Equity (ROE), Market to Book ratio (MB ratio), and Price Earnings ratio (PE ratio) and variables Board Size (BS), Institutional Shareholding ratio (ISH ratio), CEO duality (CEOD) and Board Independence as corporate governance variables while Leverage ratio (LEV) and Firm Size (FS) are controlled and included in the models as follow:- Perf(ROA) jit = ? 0 + BS jit? 1 + ISH jit? 2 + CEODjit? 3 + IDjit? 4 + LEVjit? 5 + FSjit? 6 + ? Perf(ROE) jit = ? 0 + BSjit? 1 + ISHjit? 2 + CEODjit? + IDjit? 4 + LEVjit? 5 + FSjit? 6 + ? Perf(MB) jit = ? 0 + BSjit? 1 + ISHjit? 2 + CEODjit? 3 + IDjit? 4 + LEVjit? 5 + FSjit? 6 + ? Perf(PE)jit = ? 0 + BSjit? 1 + ISHjit? 2 + CEODjit? 3 + IDjit? 4 + LEVjit? 5 + FSjit? 6 + ? Where: Perfjit= Firm Performance measured by ROA, ROE, MB, and PE ratios form firm j, ith observation at time t. ?0= the intercept. BS = Board Size ISH = Institutional Shareholding CEOD = CEO Duality ID= Independent Directors LEV = Leverage Ratio FS = Firm Size ? = Stochastic distur bance term, and all the betas are coefficients of change rate in the variables against one unit increase.III. Variables Definition Table 1 AcronymVariable NameProxies Dependent Variables ROAReturn on AssetsProfit Before Tax/Total Assets ROEReturn on EquityEarnings Available to Stockholder/Total Equity MBMarket to Book ratioMarket price Per Share/Book value Per Share PEPrice Earnings ratioMarket price Per Share/Earning Per Share Independent Variables BSBoard SizeNumber of Directors in the Board of Directors ISHInstitutional ShareholdingPercentage shares held by Institutional Investors CEODCEO DualityDummy variable, equals to 1 if CEO and Chairman is the same person or 0 otherwise.IDIndependent DirectorsThe ratio of No. of Independent Directors/Total Number of Directors in the Board of Directors LEVLeverage ratioTotal Debt/Total Assets FSFirm SizeNatural Log of Total Assets Results Table 2 discusses the descriptive statistics of all the variables including dependent variables Return o n Assets (ROA), Return on Equity (ROE), Market to Book ratio (MB), and Price Earnings ratio (PE). The mean value of PE 5. 134 is less as compared to the other dependent variables which denote the lower earnings gained by insurance companies as compared to the mean value of ROE which is 12. 91 which is almost double and depicts the picture that insurance companies earn more on equity. BS mean value 10. 654 shows that on average nearly 11 numbers of directors is part of the board having a standard deviation of 1. 108. On the average 40. 489% of all the issued share of an insurance company are held by institutional investors with a standard deviation of 6. 333%. The ratio of CEOD in the insurance industry of Pakistan is 0. 477 which expresses that on the average there are 47. 7% companies where CEO and Chairman is the same individual.The mean value of ID, 0. 425 tells about the average ratio of board independence in an insurance company in Pakistan. Leverage value of 0. 581 shows that on average an insurance company employs 58. 1% debt in the capital structure ratio. Table 2 Descriptive Statistics MeanMinimumMaximumStd. Deviation ROA9. 631-25. 63852. 78320. 035 ROE12. 791-53. 85989. 36936. 980 MB5. 1343. 427. 781. 456 PE10. 3428. 716. 62. 059 BS10. 6549121. 108 FS16. 72916. 17917. 2130. 288 ISH40. 48931. 23053. 9306. 333 CEOD0. 477010. 502 ID0. 4250. 2220. 6670. 091 LEV0. 5810. 3990. 6930. 073Table 3 models summary tells about the R-Square(s), Adjusted R-Square(s) and the Durbin-Watson values which tell about the fact that is there any auto-correlation problem? The calculated values for the models individually tell that there is not auto-correlation problem as all the values are in the range 1. 5-2. 5. Adjusted R-Square of model 4(PE) is largest 0. 897 which tells that all the covariates explain the model by 89. 7%, while the Adjusted R-Squared value of model 3 is smallest 0. 722 which explains about 72. 2% of the model. Table 3 Models Summary ModelRR SquareAdjus ted R SquareStd.Error of the EstimateDurbin-Watson 1 (ROA)0. 9370. 8770. 8707. 22601. 913 2 (ROE)0. 8620. 7430. 72819. 3001. 982 3 (MB)0. 8590. 7380. 7220. 7681. 907 4 (PE)0. 9500. 9020. 8970. 6622. 257 Table 4 tells about the individual significance of the four models used in the study. The F-value of model ROA is 119. 139 and p-value is 0. 000 which tells that the model is significant, while the F-value for model ROE is 48. 189 and p-value is 0. 000 which is significant. F-value of model MB is 48. 863 and p-value is 0. 000 which is again significant and the model PE is also significant as the p-value for that model is 0. 00. All the models are significant at 5% level of significance. Table 4 ANOVA Model Sum of SquaresdfMean SquareFSig. 1 (ROA)Regression37325. 50766220. 918119. 1390. 000 Residual5221. 53310052. 215 Total42547. 040106 2 (ROE)Regression107706. 536617951. 08948. 1890. 000 Residual37250. 738100372. 507 Total144957. 274106 3 (MB)Regression165. 773627. 62946. 8630. 000 R esidual58. 9571000. 590 Total224. 730106 4 (PE)Regression405. 554667. 592154. 0760. 000 Residual43. 8701000. 439 Total449. 424106 Table 5 narrates the Pearson correlation coefficients for the model 1 where the dependent variable is ROA.Institutional Shareholding has the largest coefficient 0. 845 which means that it has a strong positive relationship with Return on Assets. Firm size also has significantly positive relation with the return on assets. Board size unexpectedly showed a very weak relationship with the return on assets, the coefficient is 0. 048. CEO duality is another case which has a weak positive relationship with ROA, the coefficient of CEOD and ROA is 0. 034. The empirical evidence shows that there is negative relation between firm size, institutional shareholding, leverage and board size either the relations among these variables are not strong.Leverage also have negative but near to zero relation to the firm size. Board independence (ID) is also negatively associat ed to the institutional shareholding. Table 5 Pearson Correlation ROABSFSISHCEODIDLEV ROA1 BS0. 0481 FS0. 556-0. 0451 ISH0. 845-0. 2130. 3911 CEOD0. 0340. 2140. 0360. 0921 ID0. 2360. 0750. 707-0. 097-0. 0301 LEV0. 441-0. 010-0. 0010. 425-0. 321-0. 1531 Table 6 discusses the regression coefficients when the dependent variable is ROA. The results show that all the coefficients are significant except the firm size and CEO duality.Firm size has negative relation with the return on assets which is consistent with the literature. CEOD has negative impact on the firm performance when it is measured by ROA; the results are not significant but support the literature. While, Board Size (BS), Institutional Shareholding (ISH), Independent Directors (ID), and Leverage has positive impact on firm performance. There is no multi-collinearity problem with the variables as suggested by the VIF values. Table 6 Coefficients ModelVariablesUnstandardized Coefficients Standardized CoefficientstSig.Colline arity Statistics BetaStd. ErrorBeta ToleranceVIF 1(Constant)-179. 18670. 247 -2. 5510. 012** BS4. 1100. 6870. 2275. 9850. 000*0. 8501. 176 FS-0. 8464. 625-0. 012-0. 1830. 8550. 2783. 595 ISH2. 8300. 1730. 89516. 4020. 000*0. 4132. 424 CEOD-2. 2511. 620-0. 056-1. 3900. 168***0. 7461. 341 ID71. 95713. 3210. 3275. 4020. 000*0. 3342. 993 LEV26. 02312. 1630. 0952. 1400. 035**0. 6201. 613 Dependent Variable: ROA. *, **, *** show 1%, 5% and 10% significance level respectively. Table 7 discusses the Pearson correlation coefficients now taking Return on Equity as dependent variable.Again consistent with the previous model, Institutional Shareholding has the largest coefficient which shows a strong relation of ISH with ROE. COED has the smallest coefficient but has positive association with the ROE. BS has negative relation with Firm size, ISH and Leverage which in line with the literature. Independent directors’ ratio is negatively associated to the ISH but has a weaker relationship. ID has also inverse relation with leverage and also has weak relation. Table 7 Pearson Correlations ROEBSFSISHCEODIDLEV ROE1 BS0. 0531 FS0. 485-0. 0451 ISH0. 739-0. 2130. 3911 CEOD0. 0190. 2140. 0360. 0921ID0. 2890. 0750. 707-0. 097-0. 0301 LEV0. 371-0. 010-0. 0010. 425-0. 321-0. 1531 The results of some of the variables are now different form the results of the previous model where dependent variable was ROA. In the table 8, the dependent variable is Return on Equity (ROE), the reason why leverage has become insignificant. Board size, Firm size, Institutional Shareholding, and Independent directors’ ratio are the statistically significant variables. While COED and Leverage are insignificant but both have positive impact on firm performance. The Institutional Shareholding has largest beta coefficient of 0. 20 which means every 1% increase in Institutional Shareholding will increase firm performance by 0. 920. CEOD has negative impact on firm performance which is consistent wi th the findings of Masood Fooladi Chaghadari (2011). VIF values depict the absence of multi-collinearity problem in the variables. Table 8 Coefficients Model Unstandardized Coefficients Standardized CoefficientstSig. Collinearity Statistics BetaStd. ErrorBeta ToleranceVIF 2(Constant)138. 509187. 627 0. 7380. 462 BS7. 1561. 8340. 2143. 9020. 000*0. 8501. 176 FS-31. 18112. 354-0. 243-2. 5240. 013**0. 2783. 595 ISH5. 3790. 4610. 92111. 6720. 00*0. 4132. 424 CEOD-5. 4804. 326-0. 074-1. 2670. 208***0. 7461. 341 ID218. 28535. 5810. 5386. 1350. 000*0. 3342. 993 LEV20. 27232. 4860. 0400. 6240. 5340. 6201. 613 Dependent Variable: ROE. *, **, *** show 1%, 5% and 10% significance level respectively. Consistent with previous models, Institutional shareholding ratio has largest coefficient which strong relationship with firm performance. Board size, CEO duality and independent directors’ ratio found to have negative but weak relation with firm performance in this model. Independent direct ors’ ratio has negative association with Institutional shareholding.Independent directors’ ratio is negatively associated to the leverage ratio also. Firm size has strong positive relation with independent directors’ ratio; the correlation coefficient between these two variables is 0. 770. Table 9 Correlations MBBSFSISHCEODIDLEV MB1 BS-0. 0411 FS0. 005-0. 0451 ISH0. 624-0. 2130. 3911 CEOD-0. 2240. 2140. 0360. 0921 ID-0. 0310. 0750. 770-0. 097-0. 0301 LEV0. 375-0. 010-0. 0010. 425-0. 321-0. 1531 In Table 10 dependent variable is Market to Book ratio. In this model Firm Size (FS), COE Duality and Leverage have negative but significant impact on firm performance.Variables Board Size, Institutional Shareholding and Independent Directors’ ratio have positive and significant impact on firm performance. Negative coefficient of FS -0. 927 means every unit increase in firm size will lead to -0. 927 times decrease in firm performance. The results are consistent wit h the previous literature. VIF statistics show that there is no multi-collinearity problem. Table 10 Coefficients Model Unstandardized Coefficients Standardized CoefficientstSig. Collinearity Statistics BetaStd. ErrorBeta ToleranceVIF 3(Constant)67. 2377. 464 9. 0080. 000* BS0. 2590. 0730. 1973. 5540. 001*0. 501. 176 FS-4. 6920. 491-0. 927-9. 5470. 000*0. 2783. 595 ISH0. 2740. 0181. 19014. 9240. 000*0. 4132. 424 CEOD-1. 0680. 172-0. 368-6. 2070. 000*0. 7461. 341 ID11. 0621. 4160. 6927. 8140. 000*0. 3342. 993 LEV-2. 8151. 292-0. 142-2. 1790. 032**0. 6201. 613 Dependent Variable: MB. *, **, *** show 1%, 5% and 10% significance level respectively. In table 11, dependent variable is Price Earnings ratio and it shows the Pearson Correlation coefficients. Inconsistent with the previous models, Institutional Shareholding has negative and strong relationship with Price Earnings (a measure of firm performance).In this model Leverage also has strong negative relationship with firm performance . Firm Size, ISH, and LEV are negatively associated with Board Size. But only the leverage has negative relation with Firm size, CEO duality and Independent Directors’ ratio. Independent Directors’ ratio has strongly positive relationship of 0. 707 with Firm size. Table 11 Pearson Correlations PEBSFSISHCEODIDLEV PE1 BS0. 0531 FS0. 406-0. 0451 ISH-0. 582-0. 2130. 3911 CEOD-0. 1050. 2140. 0360. 0921. 0 ID0. 6680. 0750. 707-0. 097-0. 0301 LEV-0. 575-0. 010-0. 0010. 425-0. 321-0. 1531In table 12 all the independent variables are significant except for Board Size, the only variable which is insignificant but is negatively associated to the firm performance. This is also consistent with previous literature. Values of VIF tell about the absence of multi-collinearity in the variables. Table 12 Coefficients ModelUnstandardized CoefficientsStandardized CoefficientstSig. Collinearity Statistics BetaStd. ErrorBeta ToleranceVIF 4(Constant)-38. 3486. 439 -5. 9560. 000* BS-0. 0720. 0 63-0. 039-1. 1460. 2550. 8501. 176 FS3. 6760. 4240. 5148. 6700. 000*0. 2783. 595 ISH-0. 2000. 016-0. 615-12. 6330. 00*0. 4132. 424 CEOD-0. 6570. 148-0. 160-4. 4250. 000*0. 7461. 341 ID4. 3461. 2210. 1923. 5590. 001**0. 3342. 993 LEV-9. 4391. 115-0. 336-8. 4670. 000*0. 6201. 613 Dependent Variable: PE. *, **, *** show 1%, 5% and 10% significance level respectively. Conclusion Corporate governance plays a pivotal role in the performance of Insurance Companies. There are different statutory bodies in different countries which control and ensure the best practices in the corporations like in Pakistan Securities and Exchange Commission of Pakistan is responsible for monitoring and controlling such practices in the corporations.This study finds that Board Size (BS), Institutional Shareholding (ISH) and Independent Directors’ ratio have positive and significant impact on corporate governance. The reasons are if Board size is large, the board has members having diverse background, mo re viewpoints, and competitive and experienced individuals which lead towards right decision making and towards better performance as compared to the industry norms. Institutional investors have more interest in the investment and management skills which adds to the performance of the firm.The more the Independent Directors in the board, the more the transparency and integrity which ultimately leads towards enhanced performance. CEO duality have negative impact on the firm performance due to reason that inefficiencies and mismanagement in the operations is not watched by any independent person which make the performance of the company worse. The study also finds that Firm Size and Leverage also have negative impact on firm performance. As the size of the firm increases due to the reason of diseconomies of scale it puts worse impact on the financial performance of the firm.For the future research, scholars may increase the sample size to get more generalized results and there should be included more corporate governance variables like family ownership, concentration, directors’ remuneration and many others. References Najjar, Naser (2012). â€Å"The Impact of Corporate Governance on the Insurance Firm’s Performance in Bahrain†. International Journal of Learning & Development ISSN 2164-4063 2012, Vol. 2, No. 2 Zubaidah Z. A. , Kamaruzaman J. and Nurmala M. K. (2009). Board structure and corporate performance in Malaysia.International Journal of Economic and Finance 1(1): 150-164. Williams S. M. and Ho C. A. (2003). International Comparative Analysis of the Association between Board Structure and the efficiency of Value Added by a Firm from its Physical Capital and Intellectual Capital Resources. The International Journal of Accounting 38(4):465-491. Ming-Cheng Wu, Hsin-Chiang Lin, I-Cheng Lin, Chun-Feng Lai. â€Å"The Effects of Corporate Governance on Firm Performance†. Chaghadari, Masood Fooladi (2011). â€Å"Corporate Governance a nd FirmPerformance† 2011 International Conference on Sociality and Economics Development IPEDR vol. 10 (2011)  © (2011) IACSIT Press, Singapore Bhagat, Sanjai and Bolton, Brian (2007). â€Å"Corporate Governance And Firm Performance†. Kajola, Sunday O (2008). â€Å"Corporate Governance and Firm Performance: The Case of Nigerian Listed Firms†. European Journal of Economics, Finance and Administrative Science ISSN 1450-2275 Issue 14 (2008) D. N. Ranasinghe (2010). â€Å"Composition and Configuration of the Board and Firm Performance in Financial Services Industry in Sri Lanka†. DSM Business Review v Vol. , No. 2 (December, 2010) Anthony Kyereboah-Coleman (2007). â€Å"CORPORATE GOVERNANCE AND FIRM PERFORMANCE IN AFRICA: A DYNAMIC PANEL DATA ANALYSIS†. International Conference on Corporate Governance in Emerging Markets. 15th -17th November, 2007, Sabanci University, Istanbul, Turkey Shaheen, Rozina and Nishat, Dr. Mohammed. â€Å"Corporate Governan ce and Firm Performance- An Exploratory Analysis†. Nittayagasetwat, Aekkachai and Nittayagasetwat, Wiyada (2009) â€Å"Empirical Analysis of Corporate Governance: The Impact on Firm Performance: The Case of Thailand†. Patibandla, Murali (2001). Equity Pattern, Corporate Governance and Performance: A Study of India’s Corporate Sector†. J. Bacon (1973). â€Å"Corporate directorship practice, member and committees of the board†. New York: The conference board. Sanjai Bhagat, Brian Bolton (2008). â€Å"Corporate governance and firm performance†. Journal of Corporate Finance 14 (2008) 257–273 Alon Brav, Wei Jiang, Frank Partnoy, Randall Thomas (2006). â€Å"Hedge Fund Activism, Corporate Governance, and Firm Performance†. Malik, Hifza (2011). â€Å"DETERMINANTS OF INSURANCE COMPANIES PROFITABILITY: AN ANALYSIS OF INSURANCE SECTOR OF PAKISTAN†.Volume 1, Issue 3, November 201 Naveed Ahmed, Zulfqar Ahmed, Ahmad Usman (2011). †Å"Determinants of Performance: A Case of Life Insurance Sector of Pakistan†. International Research Journal of Finance and Economics ISSN 1450-2887 Issue 61 (2011). Al-Shami, Hamdan Ahmad (2008). â€Å"Determinants of Insurance companies’ profitability in UAE†. Narjess Boubakri, Jean-Claude Cosset, and Omrane Guedhami (2001). â€Å"Liberalization, Corporate Governance, and the Performance of Newly Privatized Firm†. William Davidson Institute Working Paper 419 Stuart Kells and Mark Rogers (1997). Executive remuneration, board structure, corporate strategy and firm performance: A taste of the literature†. ISSN 1328-4991, ISBN 0 7325 0955 6 Kader Sahin, Cigdem Sahin Basfirinci2 and Aygun Ozsalih (2011). â€Å"The impact of board composition on corporate financial and social responsibility performance: Evidence from public-listed companies in Turkey†. African Journal of Business Management Vol. 5 (7), pp. 2959-2978, 4 April, 2011 Farshid Navissi a nd Vic Naiker (2006). â€Å"Institutional ownership and corporate value†. Managerial Finance Vol. 32 No. 3, 2006 pp. 247-256 John E. Core, Robert W.Holthausen*, David F. Larcker (1999). â€Å"Corporate governance, chief executive officer compensation, and firm performance†. Journal of Financial Economics 51 (1999) 371? 406 Dong-Sung Cho* and Jootae Kim (2007). â€Å"Outside Directors, Ownership Structure and Firm Profitability in Korea†. Volume 15 Number 2 March 2007 Victoria Wise, Muhammad Mahboob Ali (2009). â€Å"Corporate Governance and Corporate Social Responsibility in Bangladesh with special reference to Commercial Banks†. Working Paper No. AIUB-BUS-ECON-2009-0 Gujrati, Damodar N. & Porter, Dawn C. â€Å"Basic Econometrics†. 5th Edition McGraw-Hill

Mmmm, You Dirty Rat!

Mmmm, You Dirty Rat! Mmmm, You Dirty Rat! Mmmm, You Dirty Rat! By Maeve Maddox Its the rare media mention of Wall Street con man Bernie Madoff that doesn’t contain the word rat in some context. Bernard Madoff is an evil crook but apparently not a rat. The Big Rats off to the Big House for Life, What About the Little Rats? Madoff may rat out co-conspirators They [Mr. and Mrs. Madoff] seemed to stay apart from the herd,† the club member said. â€Å"They chose not to get into that social rat race.† U.S. District Judge Denny Chin who presumably will sentence Madoff said that he’d sharply limit the number of Madoff victims who get to shake their fist in the swindler’s face and tell him what a rat he is†¦ It is almost inconceivable that Madoff could have spent 20 years squirreling away clients money in a Chase Manhattan bank account, conducting virtually no legitimate transactions, without anybody at Madoff Investment Securities smelling a rat – The etymological origin of the word rat is lost in the mists of the long history shared by this repugnant animal and human beings. (I know, white rats make nice pets. Im talking about nasty rats au naturel.) The OED offers several possible origins, but concludes: It is uncertain whether the Latin and Romance words are cognate with the Germanic words, or whether they were borrowed from Germanic, or vice versa; in any case the ultimate origin is uncertain; perhaps imitative of the sound of gnawing. The OED also offers seven entries for rat as a noun and three for rat as a verb. The literal meaning of rat is, of course, a rodent resembling a large mouse, often with a naked or sparsely haired tail. Then there are the figurative uses that derive from the fact that rats are associated with filth and that they are said to be quick to leave a sinking ship or a falling house. The sense of rat as one who abandons his associates was in use in 1629. rat as a noun rat a despicable person, especially one who betrays or informs upon associates. rat scab laborer NOTE: a scab is either an employee who works while his colleagues are on strike, or an outsider hired to replace a striking worker. rat a pad of material, typically hair, worn as part of a womans coiffure to puff out her own hair. rat as a verb rat intransitive verb to desert a party, cause, or princple; to go over as a deserter; to abandon, desert, or betray any person or thing. rat transitive verb to backcomb or tease hair rat intransitive to act as an informer; to betray to the police or other authorities rat on to inform on a person rat out to inform on a person; to betray a person to the police or other authorities Other rat words and expressions rat-fink teenage slang from the 60s. A pleonasm since either rat or fink alone can mean an informant or, as verbs to inform. rat-race A fiercely competitive race or contest; spec. urban working life regarded as an unremitting struggle for wealth ., status, etc. ratsbane arsenic rathole messy, nasty place rat-pack juvenile gang; celebrities surrounding Frank Sinatra to smell a rat to suspect that something is wrong Rat has even become a suffix to create words that mean person who frequents such and such a place: dock-rat, bar-rat, rug-rat, etc. My brother, like many Cagney impersonators, thought he was quoting Cagney when he said, with appropriate grimaces and inflections, Mmmmm, you dirty rat! According to the Wikipedia Cagney bio, what Cagney really said in the movie Taxi! was Come out and take it, you dirty, yellow-bellied rat, or Ill give it to you through the door! Want to improve your English in five minutes a day? Get a subscription and start receiving our writing tips and exercises daily! Keep learning! Browse the Expressions category, check our popular posts, or choose a related post below:Homograph ExamplesThe Letter "Z" Will Be Removed from the English AlphabetThe "Pied" in The Pied Piper