Poverty Java Poor

Poverty Java Poor This thesis examines the incidence of poverty in Central Java in the period from 1996 to 2002. Susenas expenditure data in 1996, 1999 and 2002 were used to measure the incidence of poverty based on the Foster, Greer, and Thorbeckce (FGT) index. Using the decomposition formula developed by Huppi and Ravallion (1991a, 1991b), this thesis also investigates the effects of urban and rural poverty on the change in overall poverty. The incidence of poverty was higher in rural than that urban areas before the economic crisis. However, the urban poverty has worsened more significantly than the rural poverty after the crisis, as indicated by the higher headcount and poverty gap index in 1999. Spatially, poor people were distributed unevenly across districts. There were two major clusters of poor districts: one in the eastern part and the other in the middle of Central Java. One of the policy implications from our analysis is that poverty reduction programs seem to be more effective if they are targeting the poor in specific location. Poverty reduction programs should be targeted both on rural and urban poor people with specific policy measures and instruments between the rural and urban sectors. Since economic growth is found to be very effective in reducing poverty in both rural and urban areas, growth promoting policies in general should be conducive to alleviating poverty across the country. CHAPTER 1 Introduction 1.1. Background Central Java is one of six provinces in Java Island, which is the heart of Indonesia. It is located between West Java and East Java. Administratively, it consists of 29 kabupatens (regencies) and 6 kota (municipalities). According to data from Indonesia Population Census, the population of Central Java was 31,223,258 in 2000 and 31,997,968 in 2005. Compared to other provinces, it is the third most populous province in Indonesia, with the percentage of 15.2 % in 1995, 15.2 % in 2000 and 14.6% in 2005 out of the total national population of the country. According to Indonesia poverty information data base, 19.04 % of the poor people of Indonesia lived in this area. Among other provinces in Java, Central Java has the lowest GRDP. Until 1996, the growth rate of the GRDP was approximately 7% per year. In 1997, its GRDP shrank and grew negatively due to the economic crisis. The economic crisis following the currency depreciation triggered the increase of price of basic needs, especially foods. The inflation rate in Central Java increased sharply from 5.4 % in 1996 to 10.9 % in 1997 and reached 75.5 % in 1998. This undoubtedly affected the living standard of the people. The people not only suffered from the price increase, but also lost their jobs. Many industries collapsed, increasing the unemployment rate in Indonesia, including Central Java that brought many households into poverty. 1 1.2. Objectives of Study Firstly, the objective of this study is to examine the poverty incidence in Central Java in 1996, 1999, and 2002. By calculating the incidence of poverty using the FGT measure for each kabupaten and kota, this study tries to describe the spatial distribution of poor people at the district level. It aims at finding out the most severe districts in the period from 1996 to 2002. Using the same poverty measurement, the incidence of poverty is also measured for urban and rural areas, to investigate where the poor are concentrated. Secondly, using the decomposition formula developed by Huppi and Ravallion (1991a), this study also aims at investigating the influence of poverty incidence in urban and rural areas on aggregate poverty changes in Central Java. 1.3. Organization This study has six chapters, including this introductory chapter. Chapter 2 provides a literature review of studies on the impact of economic crisis on poverty and living standard in Indonesia, and the spatial analysis on poverty. Chapter 3 presents an overview of Central Java economic performance in 1996-2002 and poverty reduction policies that have been implemented in Central Java. Chapter 4 describes the method and the data used in this study. Chapter 5 presents the pattern of poverty in urban and rural areas and pattern of poverty by kabupaten/kota. Finally, chapter six presents the conclusions. CHAPTER 2 Literature Review 2.1. The Impacts of Macroeconomics Condition on Poverty Studies on the impact of the changes in macroeconomic condition and government policy on poverty have been conducted by many researchers. Their objectives were to find desirable development policies to facilitate poverty alleviation. One of the interesting issues is the impact of the financial crisis that caused high inflation in the mid 1997. Since poverty is often defined in terms of income, price changes must have a significant effect on individuals living standard. The external shock that affected macroeconomic condition in Indonesia in the mid 1980s was the declining of oil prices which caused GDP per capita growth rates to fall sharply (Huppi and Ravallion, 1991b). To examine how this shock affected the aggregate poverty in Indonesia, Huppy and Ravalion (1991a) employed the Foster, Greer, and Thorbecke (FGT) index to measure the incidence of poverty. Using Susenas data in 1984 and 1987, they developed a decomposition formula to assess relative gains to the poor within the specific sectors and the contribution of each sector to the change in aggregate poverty. They found that aggregate poverty, both in urban and rural areas in Indonesia declined during this adjustment period. 3 Using the same data and method, Huppi and Ravallion (1991b) continued their research to examine the change in the sectoral structure of poverty in the adjustment period. They employed their decomposition formula to examine the sectoral gains due to the reduction in aggregate poverty. According to the findings, a high concentration of poverty was found in rural farming areas, therefore gains within rural farming sector had the highest contribution to the aggregate poverty reduction. An increase in rural farming sectors mean income and consumption had strong contribution due to aggregate poverty reduction. This study also found that more than a half of the gains were contributed by rural farming sector in Central Java and East Java. After the adjustment period, Indonesia was hit by the financial crisis in the mid 1997, which caused a significant decline in GDP per capita. Friedman and Levinsohn (2002) analyzed the distributional impact of Indonesias financial crisis on household welfare. They used the consumption module of the 1996 National Socio-Economic Survey (SUSENAS) as the pre crisis data and monthly price data for 44 cities throughout Indonesia from January 1997 to October 1998. They matched both data to obtain compensating variation which is the amount of money sufficient to compensate households following price changes and enable a return to pre crisis level utility (Friedman and Levinsohn, 2002). According to their finding, the impact of the crisis on household welfare depends on the consumption choice, sources of income, and location, i.e., urban and rural areas. In general, households were severely affected, and the urban poor was the most adversely affected by the crisis. Rural poor were not affecte d as much as the urban poor because of their ability to produce food to mitigate high inflation. Skoufias et al.(2000) also conducted a research about the changes in household welfare, poverty and inequality during the crisis. They used the 100 village survey data conducted by CBS (Indonesian Central bureau of Statistics) in May 1997 and August 1998. Using the social welfare function developed by Atkinson in 1970, where welfare at time t is the function of the mean level of per capita consumption expenditure (PCE) in period t multiplied by one minus the level of inequality in the distribution of PCE in period t, they investigated the changes in households welfare. They used the Foster, Greer, and Thorbecke (FGT) index to calculate the incidence of poverty, while to calculate inequality, they used the generalized entropy class of indices, the Gini index and Atkinson index. The findings of this study were that the welfare of Indonesias household decreased in the first year of the economic crisis and the incidence of poverty doubled. One of the other studies about the dynamics of poverty during the crisis was Suharyadi et al. in 2003. To obtain a complete picture on the changes in poverty during the crisis, they used a consistent series of data which were obtained from various sources. The method used for estimating the change in the headcount ratio with the poverty line equal to the food poverty line plus non food poverty line after considering the change in prices (inflation rate) during the crisis. The result was that the headcount ratio fluctuated over the period, and reached the peak in 1998 then declined until 2001. After 2001, it started to increase, but until the early 2002. This study found that there were approximately 36 million additional people who experienced absolute poverty. Suharyadi and Sumarto (2003) investigated poverty and vulnerability in Indonesia before and after the crisis. The study used the three-step feasible generalized least square (FGLS) method to investigate the vulnerability, by combining 1996 SUSENAS as pre crisis data and 1999 SUSENAS as the post crisis data with the village potential (PODES) datasets. The result showed that the poverty incidence increased significantly, and the chronic poor (the poor who have consumption expenditures below the poverty line and will most likely stay poor in the near future) increased from 20% before crisis to 35% after the crisis. ( Suharyadi and Sumarto, 2003). Using SUSENAS data of 1984 and 1990, Cameron (2000) examined the impacts of the changes in age, educational structure, and industrial structure on poverty and inequality in Java by employing the method used by DiNardo et al., (1996). This study modified the method used by DiNardo by decomposing the changes in cumulative distribution functions, Lorenz curves and generalized Lorenz curves. Following DiNardo, the decomposition was presented visually rather than in statistical form. The results show that poverty in Java decreased during the period from 1984 to 1990, but income inequality increased in the same period. Increase in educational attainment, income of less educated workers and income of outside agriculture workers contributed to the poverty reduction in Java. On the other hand, an increase in non-agricultural income and education attainment also contributed to the inequality increase. 2.2. Spatial Analysis on Poverty Poverty can also be analyzed spatially. It is a spatially heterogeneous phenomenon where poor people tend to be clustered in specific places. Geographic variation in the incidence and magnitude of poverty is due to such spatial factors as natural resource endowments and access to services including health care, education, labor and products markets (Henninger and Snel, 2002). Islam and Khan in 1986 conducted a study on spatial pattern of poverty and inequality by using Susenas data in 1976. Inequality measures used in this study were Gini ratio, Atkinson index, Theil T index, and Theil L index, while to measure poverty, they used head count index, poverty gap index and Sen index, with different poverty lines for each province. This study investigated the correlation between poverty (using Sen index) and income inequality (using Atkinson index) by categorizing the incidence of poverty and income inequality into three categories, low, medium and high. Seven provinces, i.e., Jambi, South Kalimantan, Aceh, East Kalimantan, North Sumatra, Bali, and Central Kalimantan, had low poverty and low inequality. Six provinces, i.e., Yogyakarta, West Java, West Nusa Tenggara, South Sumatra, Riau and Bengkulu had medium level of poverty and medium level of inequality. Provinces which had high levels of poverty and inequality were Lampung, North Sulawesi, East Nusa Tengga ra, Central Sulawesi, Maluku, South Sulawesi and South East Sulawesi. Jakarta had low poverty but high inequality, West Kalimantan had a medium level of poverty but high inequality, West Sumatra had a medium level of poverty and low inequality, while Central and East Java had high poverty and a medium level of inequality. To examine the effect of a regional poverty target program in Indonesia, Daimon (2001) conducted a research on the spatial dimension of welfare and poverty. He found that there were significantly different social effects of the economic crisis across geographical locations. This study used spatial econometric method to estimate the spatial poverty trap in Indonesia. The data used was the Indonesian Family Life Survey (IFLS) in 1993, which included 6,000 households throughout 13 provinces in Indonesia. Poverty target program, called Inpres Desa Tertinggal (IDT), was designed to empower the local communities. Empowerment of local communities was the key factor to remedy the targeting policy. CHAPTER 3 Overview of Central Java Economic Performance in 1996-2002 and Poverty Reduction Policies in Central Java 3.1. Overview of Central Java Economic Performance in 1996, 1999 and 2002 Located in the middle of Java Island, Central Java has a strategic position due to its regional economic development. Its northern part, which mainly has a low terrain and passed by main transportation route, has various kinds of economic activities, particularly a lucrative fishery on Java Sea. For that reason, infrastructure developed more rapidly in this area. While the southern parts main economic activity is a less productive fishery, the central part is mainly dominated by farming due to the mountainous terrain. This province consists of 35 districts, consisting of 29 kabupatens (regencies) and 6 kotas (municipalities). 8 Central Java is the third most populous province in Indonesia. The population of Central Java was 29,698,845 in 1996, 30,761,221 in 1999 and 31,691,866 in 2002. Kabupatens Brebes, Cilacap and Banyumas were the largest districts in terms of population; while Kotas Surakarta, Tegal and Pekalongan had the highest population density. The population density of those three districts was 11,734/km2, 8,609/km2, and 7,213/km2, respectively. . Generally, per capita income decreased in the period from 1997 to 1998. It should be noted that during this period, economic crisis occurred. Only three districts (Kab. Cilacap, Kota Semarang and Kab. Brebes) experienced an increasing per capita income during this period. Based on data presented in table 3.3, 1998s growth rate was negative, due to the economic crisis in 1997, which shrank the GRDP from Rp. 43,129,839 million in 1997 to Rp. 38,065,274 million in 1998. Looking at the economic structure, the largest contributor of Central Java economy was the manufacturing industry, followed by trade and agriculture The structure of Central Java in terms of employment was slightly different from the structure in terms of GRDP. As shown in table 3.5, the highest share of employment was registered by the agriculture sector, followed by trade and manufacturing. It indicated that agriculture sector had lower productivity compared to trade and manufacture. The 1997s economic crisis also had a negative impact on employment because many industries had to reduce their production cost, mainly their labor cost. The number of unemployed people increased from 552.914 people in 1996 to 599.237 people in 1997, and 831.435 people in 1998. 3.2. Poverty Reduction Policies in Central Java In 2002 central government initiated a poverty reduction program by establishing an independent board called Komite Penanggulangan Kemiskinan (KPK) or The Poverty Reduction Committee and Komite Penanggulangan Kemiskinan Daerah (KPKD) or The Regional Poverty Reduction Committee in each province. Poverty reduction policies in Indonesia are classified into two groups. The first is aiming at community development and the second includes the safety net programs. The aims of community development based programs are to create job opportunity, to develope local/regional capacity, infrastructure building, and to improve community based activities. These programs include the following programs. Inpres Desa Tertinggal ( IDT) / Presidential Instruction to Underdeveloped Villages According to Daly and Fane (2002), this is the first anti-poverty program in Indonesia. The aim is to raise the employment opportunities and household expenditures through community development. This program was targeted to underdeveloped villages in the form of a revolving block grant, where each village accepted Rp.20,000,000.00 per year for 3 years. The fund was distributed among groups of people based on each groups proposal, and should be used for productive activities. Program Pengembangan Kecamatan (PPK) / Kecamatan Development Program. Kecamatan is a sub district which consists of several villages. The Kecamatan Development Program (PPK) was a program that also included a revolving block grant, but the fund was distributed on kecamatan level. Each kecamatan is given a fund from Rp. 750,000,000.00 up to Rp. 1,000,000,000.00, which could be used to support the private sector economic activities as revolving loans or as a capital for providing public infrastructure. This program was supported by NGOs. Program Penanggulangan Kemiskinan Perkotaan (P2KP ) / Urban Poverty Alleviation Program The idea of this program was almost the same as PPK, except that this program was targeted specifically to kecamatan in urban areas. The aim is to mitigate poverty in urban areas by supporting economic activities with loans and creating jobs for unskilled workers. Each group given the fund has to return the loan within two years with low interest. 4. Program Percepatan Pembangunan Daerah Tertinggal (P3DT )/ Supporting Infrastructure Development of Underdeveloped Villages (Desa). This is the newest program which replaced IDT program. The program has been implemented by local governments and NGOs. Hence, the NGOs help to facilitate recipient groups in each of the planning, implementation, evaluation, and report making stages. Program Pemberdayaan Masyarakat akibat Dampak Krisis Ekonomi (PDMDKE)/ Regional Empowerment to Overcome Economic Crisis Impact. This is a special program to overcome the impact of economic crisis through labor intensive activities. The aim of this program was to create jobs and to build public infrastructure. Gerakan Terpadu Pengentasan Kemiskinan (Gerdu Taskin) / Integrated Movement for Poverty Eradication. This program was administered and coordinated under The Ministry of Demography / Indonesian Family Planning Board ( BKKBN). There are three targeted groups: Family This group includes poor household, the elderly, the disabled, the unskilled unemployed workers. The program provides, for example, foods, and subsidized contraception. Regional/areas Underdeveloped villages, slum areas, coastal areas are included in this category. The programs provides basic infrastructure, such as clean water piping and public toilets. It is also used to improve housing quality in these areas. Institutions This includes governments and non governmental organizations. The program is aimed at empowering these institutions in order to overcome poverty. Social safety net programs are in the second group of poverty reduction policies. These programs were made mainly in response to the 1997 economic crisis. They are aimed at meeting basic needs, by providing subsidized rice for the poor, supplementary foods for primary school pupils, and supplementary foods for children under five years old. Under social safety net programs, governments provided free health services and subsidies for primary school fees to the poor people. They also gave a specific block grant for schools and hospitals. In 2005, a new social safety net program started, after the central government reduced oil subsidy, especially a subsidy for kerosene which is widely used by poor households. Under this new program, each poor household received the sum of Rp. 100.000 per month. CHAPTER 4 Data and Methodology 4.1. Data This study used national socioeconomic survey (Susenas) carried out in 1996, 1999 and 2002. Susenas is a consumption based survey, conducted annually by the Central Bureau of Statistics of Indonesia (CBS) since 1963 (Core Susenas). In addition, there are three modules of Susenas that has been carried out every three years since 1981. One of the modules is the consumption expenditure module that captures more than 300 items of consumption expenditure for representative of 30 provinces. This study used the consumption expenditure module for Central Java that was conducted in 1996,1999 and 2002. The sample size for Central Java Province was 6,803 in 1996, 7,303 in 1999, and 7,374 in 2002, covering 35 districts. The consumption expenditure module is classified into food and non food categories. The food category consists of 216, 214 and 216 items, whereas the non food category consists of 103, 105 in 1996, 1999 and 2002, respectively. This module also presents the way those items are obtained, whether they are purchased in the market, self produced, or received as a gift. 17 All the data are in 1996 constant price because in the mid 1997, Indonesia was hit by the economic crisis that caused the growth rate of GDP to decline, from a positive 4.7 percent in 1997 to a negative 13.1 per cent in 1998. The crisis affected the living standards of the people because the inflation rate increased substantially due to large depreciation in rupiah against US dolar. In 1998 and 1999 the inflation rate was 57% and 20% respectively, but declined to 4 % in 2000. It increased again to more than 10% in 2001 and 2002. Therefore, nominal household expenditures need to be deflated using the consumer price index in 1996 as the base year. Household consumption expenditure data are very useful when we estimate individuals living standard. Many researchers have used household consumption expenditure as an indicator of an individuals living standard. The reason is that consumption expenditure is a better welfare indicator than income. The data can be used to measure poverty by setting a poverty line based on consumption expenditure. According to Central Bureau of Statistics of Indonesia (CBS), the poverty line is defined as the total expenditure in rupiah that are able to purchase foods needed to satisfy 2,100 calories energy requirement per capita per day. It is based on the recommendation of the National Workshop on Food and Nutrition in 1978, which states that in order to stay healthy, a person must consume as much as 2100 calories per day (Maksum, 2004). The method for computing the value of the daily minimum standard of living has improved over year. The poverty line was determined separately for urban and rural areas and also for each province since the basket of food items differs among urban and rural areas and provinces. The calculation is based on the average consumption of basic items, including 52 foods items and 46 non-food items. The poverty line set by BPS for Central Java in 1996 is Rp. 30,499 for rural, Rp. 40,075 for urban and Rp. 33,444 for overall (urban and rural) in terms of monthly per capita expenditure. 4.2. Methodology 4.2.1. The Measurement of Poverty In order to measure poverty, the class of poverty measures developed by Foster, Greer and Thorbecke (FGT) will be employed (Foster et al., 1984). By using the FGT index, a quantitative estimate of the effect of a change in subgroup poverty on total poverty can be obtained. The index is defined as follows: (1) where is total number of people, is the poverty line, is the total number of poor people, is the expenditure of individual and ÃŽ ± is a parameter. The formula can be redefined according to the value of ÃŽ ± . When ÃŽ ± = 0 (2) It is simply , that is the proportion of people living below the poverty line, known as the head count index . When ÃŽ ± = 1 (3) It presents the extent to which each individuals expenditure falls below the poverty line as a percentage of the poverty line. It is called the poverty gap index. When ÃŽ ± = 2 (4) It measures the severity of poverty. P2 is distribution-sensitive for any transfer of expenditure, since the square term gives a higher weight to poorer people. 4.2.2. Decomposing Change in Overall Poverty To analyze the change in overall poverty over the study period, this study uses the decomposition formula developed by Huppi and Ravallion (1991a, 1991b), where the change in overall poverty is decomposed into intrasectoral, population shift, and interaction effects. The decomposition formula is given as follows. In this decomposition analysis, we consider two sectors: urban ( = 1) and rural sectors ( = 2). (5) In this formula, is the incidence of poverty in sector i in year t, as measured by the FGT index with the parameter , while is the population share of sector i in year t. It should be noted that in this formula, refers to the population share, rather than the total number of people. presents the change in overall poverty due to the changes in the intrasectoral poverty ( = 1, 2). presents the change in overall poverty due to population shifts, i.e., due to the change in the distribution of population between urban and rural sectors. presents the interaction effect, which captures the correlation between the sectoral and population shift effects. Since this study uses Susenas data for 1996, 1999, and 2002, we analyze the change in overall poverty in two periods: from 1996 to 1999 and from 1999 to 2002. 4.2.3. Mapping the Incidence of Poverty Using Arcview GIS 3.3 (a software package), this study presents the incidence of poverty by Kabupatens (regencies) and Kotas (municipalities) on a map using the FGT index. The aim is to show the spatial distribution of poverty in Central Java, i.e., to see whether poor people are concentrated or dispersed. In order to present the distribution of poverty on a map, we classify all districts (i.e., all Kabupatens and Kotas) in Central Java into three groups: low, medium, and high poverty groups. The low poverty group includes those districts that have the FGT value smaller than , while the high poverty group includes those having the value higher than , where is the average value of the FGT index, is the standard deviation. The medium poverty group consists of those between and . CHAPTER 5 Poverty Incidence in Central Java From 1996 to 2002 5.1. Incidence of Poverty by Location (Urban and Rural Sectors) The incidence of poverty was higher in rural areas than that in urban areas in 1996 by any FGT measures (. The headcount index ()was 0.189 in rural areas, while it was 0.172 in urban areas in 1996, its means that rural areas had a larger proportion of poor people than urban areas. The poverty gap index () was also higher in rural than urban areas, as it was 0.032 and 0.029 in rural and urban areas, respectively, meaning that rural poverty was deeper than urban areas in 1996, though this was due mostly to the fact that rural areas had a larger proportion of poor people than urban areas. 22 The incidence of poverty increased significantly both in rural and urban areas in 1999. But the increase was more substantial in urban than rural areas, as the headcount index () was 0.215 and 0.227 in rural and urban areas in 1999, respectively. In 1999, both the headcount index () and poverty gap index () were larger in urban than rural areas. The economic crisis that occurred in 1997 seems to have a much larger impact on urban than rural areas in Central Java. Food prices skyrocketed because of the large depreciation of Rupiah against the U.S. dollar after the economic crisis, and many people lost their jobs due to the collapse of some industries. But the effects were much less severe in rural areas than urban areas, since many rural people were able to produce their foods by themselves, so that they could mitigate the impact of the inflation. In 2002, Central Java seems to have recovered from the crisis, as both the headcount index () and poverty gap index () decreased prominently in both rural and urban areas. The headcount index () was 0.100 and 0.099 in urban and rural areas, respectively, meaning that mere 10 percent of the people in Central Java were under the poverty line in 2002. In 1999 and 2002, rural areas had a much larger value than urban areas (0.020 vs. 0.012 in 1999 and 0.009 vs. 0.004 in 2002), even though both the headcount index () and poverty gap index () were smaller in rural than urban areas. This indicates that while rural areas had a smaller proportion of poor people than urban areas, their poverty was much more severe than urban poverty, meaning that there were a large number of extremely poor people in rural areas whose consumption expenditures were far smaller than the poverty line. 5.2. Incidence of Poverty by District (Kabupaten and Kota) and Its Spatial Pattern In 1996, Kabupaten Blora had the highest head count index (), which was followed by Kabupatens Grobogan, Wonosobo, Sragen, and Temanggung. On the other hand, Kota Magelang had the smallest head count index (), which was followed by Kotas Salatiga, Tegal, Pekalongan, and Kabupaten Pekalongan. Except Kabupatens Pekalongan, Demak, Sukoharjo, and Kudus, kabupatens had much larger values of the head count index () than kotas, showing that poor people were concentrated in kabupatens. The poverty gap index () had almost the same pattern as the head count index () in 1996. Kabupaten Blora had the highest poverty gap index (), which was followed by Kabupatens Wonosobo, Sragen, Grobogan, Magelang, and Temanggung. On the other hand, Kota Magelang had the smallest poverty gap index (), which was followed by Kotas Salatiga, Tegal, Pekalongan, and Kabupaten Pekalongan. Again, except a few kabupatens, kabupatens had much larger index values than kotas. The number on the map shows the rank of districts with respect to poverty measures within Central Java. There were two major geographical clusters of poor districts

Cost Cutting Essay

Most of us spend more than we need to for a lot of things. If you really can afford luxuries such as gourmet teas or designer clothing and still save for your future, you’re lucky. However, if you’re struggling to meet the financial goals you’ve set on your retirement roadmap, it’s time to look for ways to cut expenses—daily, monthly, and long-term. Start by seeing if you’d benefit from either of these big cost-cutting strategies: †¢If you’re paying high interest on a mortgage and you plan to stay in your home for a few years, consider refinancing.  Be sure to do your home- work to avoid closing costs that might make the move less attractive financially. †¢Reduce your credit card debt. Call the bank and try to negotiate lower finance charges. Then pay down the debt as fast as you can, starting with the high-interest debt. (See AARP’s Tip Sheet, â€Å"Managing Debt. †) It’s easy to spend money without realizing how much it adds up to over a week, a month or a year. So, to make other cuts in your expenses, try reviewing what habits, like eating lunch in a restaurant every day or buying expensive clothes, can add up to in the course of a year. Here are some places to look for cuts. Meals and Entertainment Americans love to eat out, whether it’s a daily break- fast at a pricey coffee shop or fast-food dinners when you feel too tired to cook. Keep track of where you’re eating your meals and what they cost. Bringing your lunch to work and cooking your meals for dinner are good ways to reduce food expenses on a regular basis. Movie fans can save money by renting DVDs, instead of paying admission to the theater and eating that expensive popcorn. Household and Transportation Expenses  Cable television, phone service—including your cell phone— and Internet service can add up to a tidy sum every month. Make sure you have the most economical plans available. If you’re in an area with more than one provider, comparison-shop. Energy costs are climbing and will probably continue to do so. Do an energy review of your home. Plug up drafty windows and doors with weather-stripping, insulate them with blinds or curtains, and then turn down the winter temperature inside by a couple of degrees. Consider solar heating and cooling if it’s feasible where you live. If you have central air, try to use it less. Install ceiling fans in some rooms, so you don’t have to cool the entire house. During the summer months, avoid using the clothes dryer, dishwasher, etc. during peak hours to lower your energy bill. Your biggest transportation expenses probably come from one or more vehicles. Here are some ways to cut back on those costs: †¢Car-pool to work with neighbors or colleagues. †¢Use public transportation. †¢Talk to your insurance company about ways you can lower your rate. On the highway, save money on gas by driving 55 miles per hour instead of faster. Shopping Thoughtful planning, before you shop, is a good way to reduce expensive impulse buying. Whether you’re going to the grocery store, shopping for holiday gifts, or looking for a new pair of shoes or a party outfit, make a list and decide what you can afford to spend ahead of time—and don’t buy something unless you really need it. In the supermarket, read the unit prices: is it cheaper to buy a 16-ounce box of crackers for $3. 0, or 12 ounces for $3. 10? For larger expenses such as a winter coat or a washing machine, check prices at more than one store before you make a decision. You should also check out thrift shops, especially if you know of one in an upscale neighborhood where you might get some good bargains. For Internet purchases, in addition to comparison-shopping on prices, check shipping charges. Some sites make you pay the whole cost; others will offer a deal to entice you to buy from them.

Fast Food Nation Discussion Questions

He is shocked that the greatest power house in t e world has this disease in it's system and it is right under our noses. 2. Believe that the primary goal Closer had in writing this book is exposing a America the fries, burgers, pizzas, subs, that we consume isn't what we think t is. The chicken, cows, and pigs aren't raised on a farm, slaughtered humanely, thro ugly inspected, packaged, and appears on our plates with a nice wrapper around it . He wanted us to be aware that this industry is doing everything in their power to exploit innocent workers, helpless animals, and the system with power and politics. Ink Closer is hoping for America to open their eyes and realize what is really g Long on around them. He wants to see any change, not drastic changes but slowly chaw Eng things. He might expect us to spread this information to anyone that hasn't re ad this book. To spread the info he gave to us to anyone that isn't aware of what is go ins on in their local fast food restaurants. 3 . He kind of depicts an American culture that seems to be oblivious of what is g Ongoing on and just wants to consume, consume, and consume.He kind of writes about transition of a culture where everything was made from scratch and hard word k paid off. No short cuts were taken. Nothing was ‘fast?' just quality food. (pigs 18, 1 7, 46, 50) He described American Farmers as a dying species, businessmen as money hung children as exploited adolescents, general working public as being manipulate d, and the eating public as an unaware audience. 4. The tone of Chlorate's text is subtle yet stern. I would classify this book as outstretching, dark, heartrending and informative.I honestly do not b live that anywhere in the book there was a hopefulness or optimism. It just seem to get darker and darker the more you read on. He asserts his opinion in sections like and Potatoes, The Most Dangerous Job, Your Trusted friends. Yes there are SE actions that are less/ or more biased. (Kenny pig 186, Sharp Knives pig 1 72, A Broken Link pig 146) 5. The effect of these stories is to have us feel connected in a way with them. Like e we know them personally, and understand and feel what they been through, and they are included to give us a generalization of how long these industries have been d Long these things.

Mae Jemison First African-American Woman Astronaut

NASA astronauts have a love of science and adventure and are highly trained in their fields. Dr. Mae C. Jemison is no exception. Shes a chemical engineer, scientist, physician, teacher,  astronaut, and actor. Over the course of her career, she has worked in engineering and medical research and was invited to be part of a Star Trek: Next Generation episode, becoming the first NASA astronaut to also serve in the fictional Starfleet. In addition to her extensive background in science, Dr. Jemison is well-versed in African and African-American studies, speaks fluent Russian, Japanese, and Swahili, as well as English and is trained in dance and choreography. Mae Jemison's Early Life and Career Dr. Jemison was born in Alabama in 1956 and grew up in Chicago. After graduating from Morgan Park High School at the age of 16, she went on to attend Stanford University, where she earned a BS in Chemical Engineering. In 1981, she received a Doctor of Medicine degree from Cornell University. While enrolled at Cornell Medical School, Dr. Jemison traveled to Cuba, Kenya, and Thailand, providing primary medical care to the people living in these nations.   After graduating from Cornell, Dr. Jemison  served in the Peace Corps, where she supervised the pharmacy, laboratory, medical staff as well as provided medical care, wrote self-care manuals, developed and implemented guidelines for health and safety issues. Also working in conjunction with the Center for Disease Control (CDC) she helped with research for various vaccines. Life as an Astronaut Dr. Jemison returned to the U.S. and worked with CIGNA Health Plans of California as a general practitioner. She enrolled in graduate classes in engineering and applied to NASA for admission to the astronaut program. She  joined the corps in 1987 and  successfully completed her astronaut training, becoming the fifth black astronaut and the first black female astronaut in NASA history. She  was the science mission specialist on STS-47, a cooperative mission between the U.S. and Japan. Dr. Jemison was a co-investigator on the bone cell research experiment flown on the mission. Mae Jemison in Spacelab-J Crew Training: Jan Davis and Mae Jemison took part. NASA Marshall Space Flight Center (NASA-MSFC) Dr. Jemison left NASA in 1993. She  is currently a professor at Cornell University and is a proponent of science education in the schools, particularly encouraging minority students to pursue STEM careers. She founded the Jemison Group to research and develop technology for daily life, and is heavily involved in the 100 Year Starship Project. She also created BioSentient Corp, a company aimed at developing portable technology to monitor the nervous system, with an eye toward treating a variety of related disorders and illnesses. Dr Mae Jemison attending the One Strange Rock premiere in New York City on March 14, 2018. She actively advocates for science literacy for all people. Getty Images/John Lamparski/contributor. Honors and Awards Dr. Mae Jemison was the host and a technical consultant to World of Wonders series produced by GRB Entertainment and seen weekly on the Discovery Channel. She has earned many awards, including the Essence Award (1988), Gamma Sigma Gamma Women of the Year (1989), Honorary Doctorate of Science, Lincoln College, PA (1991), Honorary Doctor of Letters, Winston-Salem, NC (1991), McCalls 10 Outstanding Women for the 90s (1991), Pumpkin Magazines (a Japanese Monthly) One of the Women for the Coming New Century (1991), Johnson Publications Black Achievement Trailblazers Award (1992),  Mae C. Jemison  Science and Space Museum, Wright Jr. College, Chicago, (dedicated 1992), Ebonys 50 Most Influential women (1993), Turner Trumpet Award (1993), and Montgomery Fellow, Dartmouth (1993), Kilby Science Award (1993), Induction into the National Womens Hall of Fame (1993), People magazines 1993 50 Most Beautiful People in the World; CORE Outstanding Achievement Award; and the National Medical Assoc iation Hall of Fame. Dr. Mae Jemison  is a member of the  Association for the Advancement of Science; Association of Space Explorers: Honorary member of Alpha Kappa Alpha Sorority, Inc.; Board of Directors of Scholastic, Inc.; Board of Directors of Houstons UNICEF; Board of Trustees Spelman College; Board of Directors Aspen Institute; board of Directors Keystone Center; and the National Research Council Space Station Review Committee. She has presented at the UN and internationally on the uses of space technology, was the subject of a PBS Documentary, The New Explorers; Endeavor by Kurtis Productions. She has actively advocated for science literacy, particularly among girls and women, and has spoken publicly about science and science education at many public events. In 2017 she was awarded the Buzz Aldrin Space Pioneer award and has been awarded nine honorary doctorates for her achievements. She also is part of the Lego Women of NASA set that appeared in 2017, joining such pioneers as Margaret Hamilt on, Sally Ride, Nancy Roman, and others. Jemison has often told students not to let anyone stand in the way of getting what they want. â€Å"I had to learn very early not to limit myself due to others’ limited imaginations, she said. I have learned these days never to limit anyone else due to my limited imagination.† Fast Facts about Dr. Mae Jemison Born: October 17, 1956 in Decatur, AL, grew up in Chicago, IL.Parents: Charlie Jemison and Dorothy GreenFirst African-American female astronaut.Flew aboard STS-47 September 12-20, 1992 as a Mission Specialist.Serves as a professor at Cornell University.Founded the 100-year Starship Project and advocates for science literacy.Appeared in Star Trek: The Next Generation and several other TV shows and films. Edited and updated by Carolyn Collins Petersen.