Economic Proposal

Economic Proposal

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CONTENTS

Introduction—————————————————————————-3

Literature review———————————————————————-4

Research questions and rationale—————————————————14

Model and methodology————————————————————-14

Regression model and source of data———————————————–15

Expected result————————————————————————19

References——————————————————————————21

Introduction

There are abundant literature resources all over the world that give information about the relationship between income inequality and institutional factors. However, there has not been a single theory that has been able to explain the hypothetical factors that do explain the relationship between income inequality and international trade. In most of the concrete resources that I came across when coming up with this article, I was able to realize that most of these do have only one or just a couple of factors. As a matter of fact, some of these studies that have been done have come up with some factors, but they do not to look deeper so as to address all the impact of international trade on income distribution in such a way that can be deemed relevant.

Increasing inequality across many nations over many years poses a challenge to economic policymakers in both developing and developed states. While developments in technology, liberal market reforms, and the integration of nations from earlier Soviet bloc into the world economy have led to high levels of integration of the global economy, the benefits of increasing incomes and aggregate GDP growth percentages associated with globalization share unequally among segments of populations. Income inequality in most countries rose over the past two decades, including developed nations, which had thought of great levels of prosperity. Much debate is on the rising inequality perpetrated by globalization-especially trade, which explains inequality patterns (Nielsen & Alderson, 1997).

From the 1970’s, most countries all over the world experienced sharp increase in income inequalities. It is also from around this time that there has been a significant increase in the number and values of goods and services that are being sold to other countries, more so from the developed countries. To be specific, international trade coupled with increased skills in information technology has been touted to be some of the major factors that have led to increased inequality in income in most countries all over the world (Chusseau et al., 2008).

The Heckscher-Ohlin-Samuelson framework is one of the frameworks that can be used to explain the reason behind the increasing rate of income inequality. According to the model, when a country exports either good or services to another country, the prices of the goods and service will increase in the home country. This will lead to a subsequent increase in the prices of all factors of production including remuneration. In the developed countries that use technology to a big deal in their production, this will lead to an increase in demand for skilled labor which leads to increase in income inequalities. However, in the developing countries, the effect could not be similar to this because production is mostly done using unskilled labor (Crenshaw, 2003).

Literature review

Many economies have faced rise in wage and income imbalances over many years. For instance, in the US, the college premium of the wages of graduates in college relative to that of graduates in high school increased by over a fifth between 1979 and 1995. The general inequality also soared: in 1971, an employee at the 90th percentile earned 266% more than one at 10th percentile. The question that abound is whether new technologies- such as computers and advances in communication led to the above inequality.

Some economists believe that technology is the major driving change, although other aspects including the fall of de-unionization, minimum wage, and globalization play some role, behind the US wage structure. This is brought about by technology skill complementary: technical change is advantageous to more skilled labor, replaces earlier tasks by unskilled workforce, and raises the need for skills. Many people see a direct causal link between technological evolution and radical changes in wage distribution in the US economy (Parke, 1999).

Another technological change of the 19th century is the interchangeable parts. It got designed to the extent of replacing skill. There are no reasons that compel technological change into bringing out skill bias. If replacing educated workers is more beneficial, new technologies should then replace workers, just as other parts did (Social Situation Observatory, 2010).

Research takes these problems into consideration and looks at the start of skilled bias and conditions under for more or less skilled bias. This paper surveys some research on technology that might give an in-sight into inequality. It touches on the links between trade and technology, technology and changes in production, and the link between labor market institutions and technical change.

Data from the database of top income shares

Among the first scholars to use data from France was Piketty (2001) who later conducted the same later on the United States of America in the year 2003 together with SEAZ. It was later that more data and calculations for other 12 countries were released.

They used information from fiscal statistics to come up with a share of revenue that was received by the people in the uppermost portions in the distribution of income. This was the source of the name top income shares. Leigh (2007) shows clearly how this indicator can be used effectively as a very efficient substitute to the formally used inequality indicators of inequalities like the Gini coefficient or even ratios such as the D9/D1 ratio (Rosser & Rosser, 2001).

From the statistical data of 1996 and 1997, one can come up with some tree facts that regard to how inequality emerged in those two years, in the nine countries. These are;

The third fact is that inequality has grown with more or less strength in deferent countries. In the United States of America, Australia, the United Kingdom, Canada and in New Zealand the graph is usually sharper than it is in the other countries like France, Sweden, the Netherlands, and Germany.

The CHELEM database

This is the data from the CEPII gives data and information on exports and imports of both goods and services by several countries all over the world.

International trade has evolved two times that are in the 1970s and later in the 1980s. In the early 1920s, the most countries grew their economies by 40 percent. Later on in the 1980s, the same rose significantly for the second time. For these years, the United States of America and Germany were the biggest traders. The same had the biggest rates of income inequality.

Using the rates of openness, one can realize that international trade is on the increase. As seen in the figure below. However, the heterogeneity in the levels of the countries still remains, but the patterns with which it has evolved in all of those countries seems to be well correlated (Lundberg &Squire, 2003).

In the 1990’s foreign trade in information technology as a service was thriving. Before the 90s, most of the exports were goods, but after the 1990s there was a significant increase in the services that were exported by the different countries apart from France. By the year 1995, Germany and France were the major exporters of services followed closely by the United States of America. Over this period of time, most countries experienced an upward trend in the increase of wages and subsequently income inequality increased significantly. For example, in the United States of America wages of those who had collage level education relative to the income by those who had up to high school level of education increased by 25% between the year 1975 and 1995. Generally, in the same period of time the overall inequality in earnings soared. For example, in the year 1971 a worker who was in the 90th percentile in wage distribution was earned up to 266 percent more income than the worker who was in the 10th percentile. By the year 1995, the percentage increased by 100 percent to a high level of 366 percent. Most economics believe that despite the fact that there are some other factors that do have led to changes in income distribution in the United States over this period of time; technology has been the main force that has driven the wage structure. This is because with increase in technology, the non-skilled workers are pushed out of their jobs and replaced by either the skilled ones or machines. Therefore, most economics view the relationship between information technologies with the shifts that have been occurring radically on the distribution of wages in the United States of America economy (Li, Squire, & Zou, 1998).

In the databases by CHELEM, there are three principles that can be distinguished. These are;

The first evolution was corresponding to the increasing rates of international trade. There was an aggregate increase in the number of accommodation services offered, tours and travel services that the countries offered. There was also an increase in tourism which increased the income of most people in those countries.

In the second evolution, there was an increase in transport services. Most countries and people moved from the common railway transport, and air travel and shipping gained more share in the market. The number of people travelling by air increased, the charges for air travel increased the number of goods and passengers being transported via the same means increased tremendously.

In the second evolution, there was an increase in the number of exports of several other commercial services. These were among others, services for communication, insurance, and information technology.

The dynamic model

I will use this model to come up with the coefficient of openness of the different sectors. This model will prove that the second regression period was a result of the increase in the international trade. However, at this time the impact the international trade on services did not have so much impact to inequality as it could have been expected because most of this trade was between countries in the north without involving the others so much (Piketty, 2001).

Assuming that the levels of inequalities are explained by international trade, international trade is usually represented the variable of openness for the sectors in the specific countries during a specific time; that is the GDP of the countries in the different sectors during similar periods of time. In this model, there are several variables that are involved. These are;

Foreign direct investments which at times can be substitutes for the other variables of openness and could possibly have a positive impact but only if there is some impact of Stolper-Samuelson.

Gross Domestic Product Per Capita also some significance impact on income inequality. According to Kuznetts (1955) there is a relationship between income inequality and the development in the economy which yields an inverted U-pattern when applied in those countries that have income inequality having been very high during its initial stages of development but the same decreases later on. So, if there is a relationship between development and income distribution gives us an inverted Kuznets curves, it is expected that the impact on the countries will be increasing (Hederman & Rector, 1999).

The other variable is the ratio between the people who are highly educated and those who have very little to no education at all. Education does have a decreasing effect on the income inequality. When education increases, that is more people do have skills, it is expected that there will be a reduction in the wage differences between the people who are skilled and those who are non-skilled. This means that there will be overall reduction in income inequality.

In my research, I noticed that the coefficient of openness varied with varying sectors in the economy. However, it can be noted that international trade does have a very important and an increasing effect on the distribution of income.

The coefficient of openness variable is higher and even more significant if the period in which the study was conducted was shorter. Focusing on the period from the year 1980 to 1998, there are more than two folds the coefficient that is realized for the whole period (Cornia, 2001).

The impact that international trade has on income inequality depends a lot on the countries that were studied. In the European nations, there is a very big significance in the coefficient of openness variables but this was so only in the European nations. This difference between the Anglo-Saxon countries and the countries in Europe gives a good explanation as to the non-consensus in the available literature that links international trade to inequalities in international trade.

Retrieved from http://www.motherjones.com/politics/2011/02/income-inequality-in-america-chart-graphResearch questions and rationale

How does international trade relate to income inequality?

What is the relationship between information technology and income inequality?

Rationale

The contribution of the effects of studying international trade on income inequality

The contribution of effects of studying the influence of information technology on income inequality

The above research will help future researchers on income inequality and institutional factors. Students will also benefit from this study as it will bring out the relationship between technology and income, international trade and income. Recommendations from the research will get place a in various nations. Nations might have the chance of implementing practices aimed at fighting income inequalities. The research also will support existing researches on the same topic and shed more light where information is scarce. The paper will answer questions on income, technology, and international trade that have remained mysterious for long.

Model and Methodology

Economic model

An economic model forms a simple description tool for reality used by economists. It is made in a way that gives hypotheses about an economic behavior that one can test. Economic models have subjective designs because there are no objective measures of economic results. Different economists make different views on the needs of explaining interpretations of reality.

There are two main categories of economic models. They are: empirical and theoretical. Theoretical models have verifiable information about an economic behavior under the assumption that agents capitalize on specific goals subject to constraints well defined in the model (like an agent’s budget). The give answers to specific questions-like the effects of asymmetrical data (when a part of a transaction knows more than the other) or how market failures get handled. However, empirical models aim at confirming qualitative predictions of theoretical models and changing these predictions to precise results (Chang & Ram, 2000).

Economic models have a set of mathematical equations that talk about a theory of economic behavior. Model builders include enough equations that provide useful hints about how rational agents behave and how an economy works. The equations get structured in a way that reflects reality. Some economic models are quite simple in nature. Others are rather complex: models that predict the real level of output of an economy use many complex formulations that go by names such as nonlinear, interconnected differential equations (Gustafsson & Johansson, 1997).

Regression model and source of data

A regression is an analysis of the link between two variables. It gets used in finding the relationship between the two variables.

Regression formula:

Regression equation (y) = a + bx

Slope (b) = (NΣXY – (ΣX) (ΣY)) / (NΣX2 – (ΣX)2)

Intercept (a) = (ΣY – b (ΣX)) / Nwhere               x and y are the variables.              b = the slope of the regression line               a = the intercept point of the regression line and the y axis.               N = Number of values or elements               X = First Score              Y = Second Score              ΣXY = Sum of the product of first and Second Scores              ΣX = Sum of First Scores              ΣY = Sum of Second Scores              ΣX2 = Sum of square First Scores

The variables are: corruption, technology, government policies, trade, trust, age, time,

Image on Linear regression

Period for the regression model

The period that the above research will take is two months.

The research methodology used is personal interviews, administering questionnaires and use of internet. Open ended questionnaires get the preference. This is because they give informants choices of giving more detailed information questions might not cover. Permission will first be sought from various relevant institutions before questionnaires get disseminated. Another way of collecting data is through personal interviews. A research team will be formed that will go round conducting interviews on the income inequality and institutional factors. The internet forms another means of collecting data. Questions get posted on the net and people all over the world answer according their own will and wishes. Earlier researches will also form part of information source (Scott, 2004).

This proposed research mostly studies the exploratory qualities of primary data collection, in addition to quantitative analysis approach, to data collection. This research will seek to further the already existing knowledge in the effect of institutions on income inequality, and distribution of the same. There are numerous studies that have been conducted in this field.

In addition, from the institutions’ point of view, they have taken numerous steps that would ensure that there is in reduction, in income inequality. There is a need, at times, to recognize the effort that they do to the society. Some of these institutions have done extremely well to ensure that there is a reduction in income inequality, but they find themselves on the receiving end. In other cases, some of these institutions need support from the people so that they can be yield the desired impact.

I will also seek to know the opinion of several peers in the field of economics so as to know what their opinion is, and to get more information about their opinion on the same. This will give me more information on the relationship between international trade and income inequality. Some peers could have adequate information that can be advantageous to my research, or even go to the extent of shaping the path I will use. This is because some peers have done a lot of research in several fields; therefore, if they are quite philanthropic in giving me the information they have I could get to know new models thus facilitating my own research for better results.

Data Analysis

The research will incorporate both qualitative and quantitative data analysis approaches. Focus group data will be summarized into charts, maps and other familiarization thematic frameworks.

When analyzing the data, descriptive statistical methods will prevail since data and information from several different sources will get converted into useful information that makes scientific sense. Data will get analyzed from different sources with the aim of coming up with models that will give statistical analysis of research.

Measures of central tendency will get be calculated from the data collected; the mean, mode, range, and median. Moreover, measures of dispersion such as standard deviations, variances, co-variance will also receive a precise calculation. I will also come up with graphs, polygons, histograms, percentiles; inter quartile ranges, and examples to bring forth all my points in the proposed research. Finally, proves, results and worked out problems will form integral and part of my research in an attempt to expound more on my points and ideas (Gilson & Perot, 2011).

Expected results

This research will seek to provide answers to the research questions mentioned above. By the end of the research, I expect to come out with the following results;

1. That there is adequate evidence proving that information technology does have significant impact on income inequality.

2. That information technology has significant impact on only some specific sectors in the economy and the same is very different across several countries.

3. And finally that at times when information technology is significant, the relationship between information technology and income inequality it is in most cases the same for all the sectors in the economy in the same country but different in different countries, more o, there is a very considerably big difference between the developed and developing countries.

References

Cornia, G. A., Kiiski, S. (2001) Trends in Income Distribution in the Post-World War II Period. UNU/WIDER Discussion Paper No. 2001/89.

Chang, J. Y. & Ram, R. (2000) Level of Development, Rate of Economic Growth and Income Inequality. Economic Developmentand Cultural Change, 48 (4): 787–799.

Crenshaw, E. M. (1993). Polity, Economy and Technoecology: Alternative Explanations for Income Inequality. Social Forces, 71 (3): 807–816.

Gilson, D. & Perot, C. (2011). It’s the Inequality, Stupid. Retrieved fromhttp://www.motherjones.com/politics/2011/02/income-inequality-in-america-chart-graph

Gustafsson, B. &Johansson, M. (1997). In Search for a Smoking Gun: What Makes Income Inequality Vary Over Time in Different Countries?LIS Working Paper No. 172.

Hederman, R. & Rector, R. (1999). Income Inequality: How Census Data Misrepresent Income Distribution. Retrieved from http://www.heritage.org/research/reports/1999/09/income-inequality.

Li, H., Squire, L. & Zou, H. (1998) Explaining International and Intertemporal Variations in Income Inequality. The EconomicJournal, 108 (446): 26–43.

Lundberg, M. &Squire, L. (2003). The Simultaneous Evolution of Growth and Inequality. – The Economic Journal, 113 (487): 326–344.

Nielsen, F. & Alderson, A. S. (1997). The Kuznets Curve and the Great U-Turn: Income Inequality in U.S. Counties, 1970 to1990. American Sociological Review, 2: 12–33.

Social Situation Observatory (2010). Distribution of market income. Retrieved fromhttp://www.socialsituation.eu/monitoring-report/income-distribution/distribution-of-market-income-in-the-european-union

Parker, S. C. (1999). Income Inequality and the Business Cycle: a Survey of the Evidence and Some New Results. Journal of PostKeynesian Economics 21 (2): 201–225.

Piketty T. (2001). Les hauts revenus en France au 20ème siècle. Paris:Grasset.

Rosser, J. B. & Rosser, M. V. (2001). Another Failure of the Washington Consensus on Transition Countries: Inequality and Underground Economics. Challenge 44(2): 39–50.

Scott, W. R. (2004). “Institutional theory” P408-14 in Encyclopedia of Social Theory, George Ritzer, ed. Thousand Oaks, CA: Sage.