Assignment #9

15 Nov

I think this chapter is by far the most interesting one I have read in this book. it started with describing the paradox that in rural areas of India, people who need money would rather go to informal sources, such as the moneylenders than to formal source. This poses two interesting questions.  Now that money lenders charge notoriously higher rate of interest, why are some many people still willing to borrow money from them?  It is quite obvious that banks would capture much market share if they can kick into the market by providing lawns to people, making both profits and contribution to social welfare, why we don’t see a lot of banks doing so?

It turned out that the whole picture of the story is much bigger and more complicated than we assumed. The author point out that it is quite reasonable for poor people to get loans with much higher rate from informal sources. First of all, it definitely has very much to do with the probability of the borrower defaulting on the loan. Since poor people usually are perceived to be more likely to default, it is almost necessary for the money lenders to charge higher rate on them. Secondly, the indirect cost of collecting information and putting pressure on the borrower almost push banks away from this business. Money lenders have much more flexibility in both collecting information about the borrower, and in using all types of threats that keep the borrower from defaulting. The structure under which banks are organized almost prohibit them from lending money to rural poor people, because they do not enjoy the flexibility of the moneylenders.

However, it is also possible for Microcredit to work better in the rural setting of countries like India. Knowing the unique qualities  of the borrower group and the advantages enjoyed by their counterpart, Microcredit should need much adaptations so that it is more effective, as the author argued. Actually, it is already a form of financing that is helping the poor. The consensus is, even though the updated mechanism of Microcredit does play a significant role in providing more access to funding and releasing pressure on borrowers, the impact of it on empowering under-educated women and inspiring entrepreneurship is still exaggerated to certain degree.

The stats that are presented in this chapter are generally straightforward. For example, the numbers used in the first part of this chapter create a drastic difference between the cost of borrowing from moneylenders and banks. It is used to dramatized the paradox that such a market was not tapped even with huge demand.  I think most of the statistics are trustworthy because I have read some other articles that discusses the credits cost and availabilities in India, and they basically argue the same thing.

Assignment #6

5 Oct

Title: formal outline of term paper

Student name: Chang Su

Course:  Economics 350

Instructor: professor Erin Fletcher

Here are the different sections that I intend to include in my final paper.

Introduction:

In this paper, I would like to study the effect of government’s investment in massive public projects and operations on CPI in developing countries on a cross-country level. Moreover, I would like to create a control group consisting of developed countries to compare the results of both groups. This latter treatment is designed to find whether the effect of similar action of government spending would have homogeneous effect on CPI to both developing and developed countries.

Motivation:

In this section I would like to take the chance to further illustrate the significance of this topic, and what kind of implications it would probably show to government of developing countries. First of all, many public projects that require tremendous investment would not be possible without the financial support of the government. They are necessary because they would greatly improve the basic civil infrastructure, such as the high-speed railways network in China and reservoir  constructions in the northwest India. However, macroeconomics models from intermediate class is not sufficient to provide us with detailed quantitative  measurement of the influence of “every penny spent” , and specifically, the influence these investment may have on the purchasing power of people. This is exactly what I am interested in answering.

Literature review  

Sufficient literature could be found that mainly study the output effect of government spending and its influence on many macroeconomics indicator such as inflation rate. I found the following papers specifically related to the question that I am asking here, and I would like to refer to these papers as the theoretical support in mine.

Economic Gain and Loss from Public Infrastructure investment. The author applied Computable General Equilibrium model to analyze the effect of transportation investment on Korean economy. The results shows that infrastructure investment could support economic growth, but it also has the disadvantage of price inflation. This is the main point that I intend to showcase by my regression model.  

Infrastructure Investment and Growth: Some Empirical Evidence . In this paper  the author was trying to access the relationship between infrastructure investment and economic growth by including the data of expenditure in infrastructure as  a share of GDP in traditional growth cross-country regressions.

Public Investment, Private Investment and Inflation. In this paper the author was discussing the short- and long-run effects of cutting investment in social infrastructure in a simple perfect foresight model.

The Growth Impact of Intersectoral  and intergovernmental allocation of public expenditure: with applications to China and India.  The author argues that fiscal decentralization and provincial economic growth could be both negatively or positively related.

 

Data and Modeling

Most of the data that I would use in this paper are from the databank of the World Bank. In constructing the model, I would utilize OLS in multiple regression estimation and hypothesis testing.

 

Bibliography

 

EuiJune Kim, (1998). Economic Gain and Loss from Public Infrastructure investment. Growth and Change, Vol. 29 page 445-469

 

Edward F. Buffle, (1994). Public Investment, Private Investment and Inflation. Journal of Economic Dynamics and Control , 19 (1995) 1223-1247

 

Tao Zhang& Heng-fu Zou, (2001). The Growth Impact of Intersectoral  and intergovernmental allocation of public expenditure: with applications to China and India.   China Economic Review 12(2001)58-81

 

Blanca Sanchez-Robles, Infrastructure Investment and Growth: Some Empirical Evidence . JEL O40, E62

 

 

Assignment #4

20 Sep

Personally I think it is kind of hard to summarize exactly the thesis of one chapter without knowing the general structure of the book, but there are a couple of direct points that the author made here that I think are worth noticing.

First of all, the author mentioned conventional wisdom, which he further argued to be usually different from truth. Conventional wisdom can be created and manipulated for different purposes. This conventional wisdom provides the tendency for us to believe in what seems to be easier and comfortable. He gives a famous example of Snyder, who gave a group of  deceitfully deliberated information on the homeless situation of American in Early 1980s. The statistics given here seemed to be blatantly wrong. The author easily made us believe that the fact that 45 homeless people die every second was more than absurd. I think “45 people” and “1 second” are those false statistics that could be a very supportive to the formation of conventional wisdom. If we are biased to think that homeless people are in a much worse situation than ours, we would probably not think very carefully what the implication would be if they are actually true. As long as the number fits our presumption, we would accept it.

The author then were focused on answering a “good question” (by his definition). The question is, what is it really like inside the business of gangs? does the seemingly lucrative business of drug dealing really benefits everyone in the business as we imagine? The author argued no, and he drew to other analogous industries, such as professional sports. He used the study of Venkatesh on a gang in Chicago to make his argument that, just like many other business, you have to be on top of most others to be well paid. If you are at the bottom of the pyramid, the benefits are normally so small that considering the dangers the job faces, it is not really rational to work in the position. He mention many contrasting numbers. For example, in the franchises of the gang, there were about 5300 low-file workers under 120 boss; The average annual income among top 50 bosses are more than 500,000 dollars a year, while most foot man makes 3.3 dollars an hour; the possibility of a foot man getting killed in work is almost 25%….all these statistics helped enhance the authors argument that job of a foot man is not really worth it, and you have to climb up to the top of the ladder to enjoy the huge benefits. I think the statistics are believable, and I like the author’s way of interpreting them. The drastic difference between numbers in different groups help me “visualize” the awkward position of a foot man  and get to the author’s conclusion almost naturally.

Assignment #3

14 Sep

In my research paper, I would like to study the effect of government’s investment in massive  public projects and operations on the country’s CPI in developing countries. First of all, we need to be clear about the nature of such action. Given the different stage of development, government’s investment in sectors such as, transportation, agriculture and power generation is very necessary  in that it would directly influence the living standard of general public. More importantly, projects buttressed by government in basic infrastructure development could be a substantial support to the economic growth in many developing countries. For example, the Ministry of Railways of China invested more than 100 billion dollars in 2011 on network expansion, which is approximately 1.4% of the total GDP that year.( data from http://www.zgjtjj.com/show.asp?id=7846)

By simple macroeconomics theory we know that, such huge concentrated government expense would increase the GDP(all other factors remain constant. Even though in reality, more jobs are normally created, which means consumption would increase, and investment from the project-related private sector would increase too ). So the CPI is also likely to change at the same time. I intend to find a quantitative notion of the coefficient in this relationship, so that we can measure the change of purchasing power of consumers when such projects and operations are implemented. I am interested in and motivated by this issue simply because my country, China, applies this method a lot to help partly maintaining steady economic growth(which is already slowing down this year). I would like to know how much we are really better off by looking at our real purchasing power through CPI.

My hypothesis is that, there is a positive relationship between the government investment in public projects and operations and the CPI. Hopefully from the result I can further argue that the rate of growth of our purchasing power is not as high as that of the growth of the “bigger pie”. In terms of collecting data, I would like to use the World Bank data sets because it provides both projects and operations statistics of different countries( http://www.worldbank.org/projects/country?lang=en), and inflation and consumer price(http://data.worldbank.org/indicator/FP.CPI.TOTL.ZG)

Assignment #2

7 Sep

I like the way in which the author presents a argument in this book because many specific examples and illustrations are provided and it helps lead the reader naturally to the argument. However, this method may be not so convincing as logical development because variations exist in samples and readers would automatically doubt if it qualifies as a good representative of the whole population. I think in the book the author gives many interesting statistics and I would definitely want to know more about how these data are collected and where to find them.

It seems to me that, while I was reading, the author would always threw a number in when I was not so convinced about what he just argued. So I guess the author knew exactly where he needed to add data to convince his reader, and apparently that’s the rule that he did follow. My only question is that, there are a few factors of this issue that could hardly be quantified, or even interpreted directly from data. For example, the diet structure of people obviously changed drastically during the past few decades. What do people think about being fed enough or how they should be fed are points that varies so much. How can we incorporate these variations into the interpretation of the data so that the argument would be less debatable? I think this is something I need to think of in my own term paper. Because essentially, the study of social science can not completely avoid being subjective at certain degree, but in my model, I would like to minimize this factor and thus have a better one.

Assignment #1

30 Aug

I had my first  blog account when I was in high school, and I was writing pop music reviews that became quite popular among my friends at that time. Blogging was probably the fastest way for anyone to communicate their ideas with a group of readers before twitter was created. However, blogs are normally much longer than twitter post, which also enable the writer to render an idea more systematically with journal-like structure and details. Writers have more freedom in composing their blogs. This usually make the articles more reader-friendly and accessible. But less restriction in format does not necessarily make the content less serious. For example, Paul Krugman blogs on various social, economic and political issues for The Opinion of New York Times, and personally I think most of these blogs are also academically valuable.

One specific blog that I looked up was http://espin086.wordpress.com/. The owner of this blog is a specialist in data management and statistical analysis in both payment and retail industry. He categorized most of his blogs in accordance with their topic such as ” econometrics, linear programming and operations research. On average he would blog at least twice a month. I found most of his blogs interesting, and most importantly,  easy to understand. I guess this is maybe because that most his blogs were about the results and experience he gained through working in multiple projects. Unlike working in academy, the client to whom the results were usually presented were probably not able to understand every complicated step involved in the process. So the author was obviously very good at reaching his conclusions in a solid way but also explaining things as easy as possible.