Empirical study preparation based on Woolridge, Introductory Econometric

What are the preparation that we need before starting the empirical study? As, we know that empirical study dealt with the relationship of variabels that is the relationship between the dependent variable and explantory variable. You might interested in study how education effect wage? Whether high education will raise wage? Or you might interested if there is any wage discrimination between mail and female? or You might interested how police expenditure reduce crime rate? These example give the core concept of econometric studies. In the followings, I am going to summary all I have read for two semesters for Master Course at Nagoya University, basing from Woolridge Text Book, from Chapter 1 to Chapter 19.

But what is the preparations need before we can run our study on such project?
1-First we need data. Collecting dat might sound a simple thing to do only at some cost. However, technical problem of data is sometime hard to remedy. Here, I would like to present some problem of data based on Woolridge text book of introductory econometric. One of the problem is known as mesurment error This is a kind of problem that we sometime can not get the data we expected but in stead we have only the data we observe. For example, when we collect data on income or saving we might not get the right anwer from our survey since some households might be unwilling to report their true income maybe because they try to avoid paying high tax or because of any other kinds of reason we might not get the right data we expected. In such situation if we still use the OLS regression we might get the bias estimetor if the error is correlated with the variable interested. The problem of mesurement error can be divided in two kinds. One is the mesurement error with dependent variable and another is the mesurment error with explantory variable. The error here can be given example as follow: suppose that household income is 1000 dollars but he report 900 dollars, then 100 dollars is error. For the problem of mesurment error with dependent variable the problem is not serious as long as the error is uncorrelated with the dependent variable we will get the unbaised and consistent estimator using OLS. However, if the error is correlated with the dependent variable we cant help only to recollect the right data. For the problem of measurement error of explantory variable the problem is a little tricky. There are two possibilities here, one if the variable interested or reported is uncorrelated with error then we still obtain unbaised and consistent estimator only at the cost of large variance and standard error of estimator. What happen if the reported explantory variable is correlated with error then the problem is quite serious although the bias of estimator is attenuation approching zero. So what is the soluation in this case? We can recollect the data or we can used the Instrumental Variable (IV) and two stage least square (2SLS) to obtain the right estimator.

2-The second preparation is the problem of choosing the explantory variable to include in model. From basic econometric we already known that if we fail to include enough variable we will not get the unbaised estimator. Therefore, we have to try to include all explantory variable in the model to make the model complete. However, inlcuding variable should be taken account of problem of multicollinarythat is the problem of large variance of estimator. Anyways, what we wish is to get the right estimator for the coefficient of explanatory variable. Therefore, we seek to include all explanatory variable as many as possible. The problem occure is sometime we can not use the explantory variable itself becuase the variable is unobserved then we have to use the proxyin stead. The problem of failure to include enough explanatory variable is also called endogentiy problem. Actaually, we can test to see wheather our explanatory variable is endogenous or exogenous by using statistical test. In some serve situation we might not be able to choose the right proxy for our purpose. In such situation if we wish to use OLS regression we will get the baised estimator. However, we can use the 2SLS or IV method to get the unbasied estimator.

3-Problem of misspecification of model One of my friend study at Graduate school of International Development (GSID) always ask me why in some case we need to use logarithsm form while other case we need simple linear one. These are problem of model specification. In econmetric class, I have taken with Prof .Sonota or with Prof. Fujikawa I ask him very often about this. According to the text book of Woolrdige I have read, It said that using log is prefer as we can be sure that log is not suffer from scaling in unit (say from 1 thousand to 100 thousand units), using log lead to more normal distribution (This can be test on heteroskedacity), using log is convineint for variable that is positve such as income. What is important I have read from text book, it stated that we can test for the form specification of model that use log, quatratic (parabolic) or linear format using some test such as Ramsey Test (RESET) or David-Mckinon Test. We can also used adjusted R-square to choos between model or using F-test to test non-nested model.

4-Problem of outlierSometime outlier lead to incosisten of estimator although we can apply law of large number or Central Limit Theorem (CLT). By romoving the outlier we can get the consitent estimator. Some statistical sofware package offer us such user-freindly tool.

5-Some problem with Guass Maskov Assumption for OLS There are six assumption before we can use Ordinary Least Square Regression (OLS). Let me go throuhg each assumption and mention it’s failure and solution.
Assumption 1: The model must be linear in term of paramter. This is a very basic assumption. So what happen if the explantory variable and dependent variable related with one another but not in linear form. Then, we can not use OLS regression, however, as developped by mathematical tool, in the neighborhood that is the small interval of all variable we can linearized all kind of function into linear form that make sense for our purpose.
Assumption 2:Randomness: It is quite important that we prefere random variable. In natural sicence we can have experiment that is stochastic but in social sicence the assumption might be violated. Especially in the case of time-series and panel data. Why data is not random and what is the consequence if data we collect is not radom? Data is not random is due to we select sample best on some qualification. This sometime call strata in survey and sampling method. The qualification is defined by dependent variable, indpendent variable (explanatory variable) or other related to these two variable. For example, we are willing to study the effect of training on worker productivity but we might select only firm that have training program or we might select firm that have huge capital. These lead to small sample size. Or We wish to study the effect of education on wage discrimation but we select only some group of people that have income over some range. According to the text book with proof that I excluded here said that exogenous sampling that is sampling based on qualification of explanatory variable is not a serious problem we still get the the unbaised estimator using OLS. However, endogenous sampling where sample is select based on dependent variable serious and lead to bias estimator.

Assumption 3: No perfect collineary exist between explantory variable. Perfect means variables are not related in linear function however they can related in other form of function i.e non-linear form.

Assumption 4: Exogenous Assumption: This is quite important in OLS. We have both strict and weak exogenity. Actually we can test for exogenous as I mentioned earler. The core concept here is that each variable is uncorrenated with error terms. Assmuption 1 to 3 is basic for unbasied estimator.

Assumption 5: Homoskedacity: This is important for obtaining the standard error term of each estimator. Witout this assumption we can not calucate the varaince of estimator and its standard error, therefore we can construct confidential interval or t-test or F-test or even LM-test. Therefore, what we need here is we have to ensure that our sample will ensure a costant variance. We can also test to see wheather our data follow homoskedacity or heteroskedacity using Bruece Pegan (BP) Test or White Test.. Sometime we can reject the test and thus accepting that we have heteroskedacity in our sample but we still have two solution. One we can robust the t-test, F-test or LM-test. This is the most simple method run by most sofware. In some case if we know exactly the shape of the distriubtion of error term or the exact function we can use General Least Square (GLS) or Feasible GLS (FGLS) in stead of OLS. Most sofware package provide us with these tools.

Assumption 6: Normality of error term distribution. This assumption is need to ensure that we can use t-test or F-test. However, this assumption can be relaxed if the number of observation in the sample is large enough. That is we can use the asymptotic t-test, F-test.

6-Problem with Time series data and Panal Data With time series data we have to consider addition assumption in addition to 6 assumption we have so far for cross-section data. The first I am going to talk now is the problem of serial correlation problem.
Serial correlation (SC) is problem where error term in one period correlated with error term in another time period. This occurs only in time series data. We can test to see whether our time series is serila corrlated or not using some statistical test. The test name Durbin Watson (DW-Test) can be used to test for serial correlation. Why serial correlation is so important issues in time series regression? This is because SC will cause give us bias estimator. A very simple SC occur in the form where error term appear in Autor correlation of order 1. AR(1) and the unit root case in which we have random walk for the error term. So after we test for SC if it happen that our time series suffer from SC we have two solution. First solution we can roubst SC. An alternative soulution is we can use correction the SC of form AR(1) by quasi-different and using GSL to obtain the estimator.

7-Problem with Panel Data: Panel Data is classified into two category. The pooling crossection data (a kind of data where each observation is randomly selected for each time period) for example, in year 2007, 300 household being selected to get income reported then in 2008 we selected another 300 household to get income reported agains (some previous household might be included). This kind of pooling cross-section data we can apply OLS as we did with cross-section and time series. A powerful method to deal with pooling cross-section data is to include dummy variable for each time period in population model.
Another category of panel data is a panel data where each individual in the sample is being asked again and again every time period. As this process violate the random property we can not apply OLS regression as we did with cross section and time series. However we have soultion for such kind of data by using First Different (FD), Fixed Effect (FE) or Random Effect (RE)..

All the above description is all the preparatio we should think of whenever we want to run any empirical analysis project. Most of the idea, I summarize from text book of Woolridge Introductory Econometric 2006, 3rd, Edition.

Static, Comparative Static and Dynamic Studies in Economics

The term static, comparative static and dynamic is frequently appear in economic analysis. It is the fundamental discipline that economist must have in advance before writting or reading any paper in this field.

What is mean by static, comparative static and dynamic study?
The word static originate from the field of physic. It is used to denote some kind of movement in which speed is constantly maintained. Alike, in economic static mean the studies focus only on particular period of time. It is similar to taking a photo when you press the button for a shot then the photo is just at a particular point of time. In economic most paper is a static analysis, for instance, we say the market is in equilibrium when demand and supply equate one another, which is graphically represent by the intersection point of demand and supply curve. This is a static analysis since we just only see the picture at a point of time.

Dose the equilibrium point will remain there for long? Is there any force that can push make the equilibrium move to new one or disequilibrium one? Or simply before arriving at the equilibrium what is the path that demand and supply have to change? These question can not be answer by static analysis.

Comparitive Static is a studies which focus on the external force that make the equilibrium in the model change. The external force here refere to exogenous variables. In economic we have two types of variables: endogenous and exogenous variables. Endogenous mean any variable define within the model whereas the exogenous variable refere to constant term or parameter where its value is defined outside the model. Let give a simple example of comparative static study: The keynsain model of IS-LM which represents both equilibrium in goods market and money market is a very convenient example of comparative static.

Suppose there is an equilibrium in good market that is aggreagate demand and aggregate supply equal. According to Keyn the equilibrium in goods market define equilibrium level of output and interest rate. The level of output then represents a level of empolyment. Keyn beleive that labor market is unclear-that is the supply of labor exceed the demand that why we always have unemployment. Labor market is unclear because wage is rigid in the short run (a contract between woker and employer prohibit the wage to change in the short time).

As labor market is unlcear then the government play role in creating job through fiscal and monetary policy. Fiscal policy is applied through taxation and goverment expenditure. In macroeconomic it is called multiplier effect.

Returning to comparative static, let suppose the good market is in equilibrium then suppose the government want to increase more output then it needs to increase more employment by using the government expenditure then the equilibrium will move to the new one as the expendiure is the exogenous variable change. Comaparative static is similar to taking photos at many different point of time.

How about dynamic anlysis? Dynamic we focus on the change of time and how the equilibrium change with time. It is the same as watching the movie you can see how the image animate and movement. Dynamic analysis allow us to see the path of variable how the variable change with time. It help us to see wheter the equibirium will reach or not. In dynamic economic the study of time path of variable is to see wheather the variable will converge to a point which we called stable or steady state or will it diverge (the saddle point). The detail for the study of dynamic economic is useful in advance marcroeconomic. You can familiar with it by reading textbook such as Advance macroeconomic by David Romer or Economic Growth by Robert Barro and Xala-i-Martin. However the material is quite difficult becuause the mathematical such as differential equations or optimization control are highly advanced.

In summary, economist have to choose which kind of study they prefere before starting to write the paper. For my case static or comparative static is enough. How about you?

The detail I wrote here is mainly based on Alpha Chang, The Fundamental Mathematical Economics

Problem of Moral Harzard and Adverse Selection in Financial and Insurance Industry

I used to read text book in Microeconomic Intermediate and Microceonomic Analysis of H. Valrian, in chapter dealing with uncertainty and economic of information there emerge the word Moral Harzard and Adverse Selection. He mentioned that these two component is critical in the financial market and insurance industry where information play important role in market mechanism. What is Moral Harzard or Adverse Selection? Why these two elements lead to failure in finacial market such as banking, insurance and pension system?

The term Moral Harzard as it imply is something related to morality but in what way? In fact, the word moral harzard refers to the conduct of individual in a way that he/she is able to do something that firms can not observe due to the lack of information and cuase destructive effect on other. For convinience, I give an example from Text Book of Mankiw, Macroeconomic. He gave an example of company that is trying to promote efficient by raising wage. The problem is firm can not know exactly whether workers work at 1oo percent his ability then it is subject to wrong offer incentive. Further, individual might pretent to work hard in the presence of supervisor. Another easier example is given by most economic text book is in the insurance industry, a driver who buy insurance against accident, after subscribe the insurace might even cause more accident because he thinks he now have insurance and give little care on accidence. You might have heard story about people who burn their house to get firer insurance. These are all example of moral harzard. Becasue of moral harzard most insurance company set new policy to ensure that those who buy insurance bear some part of the risk they sell to the company.

Turn to Adverse Selection, What dose this word mean? This word has long born from one economist named, Goerge Alkolof when he discover problem in used car market. Popularly known as lemon (brandname of car in US) problem. The field is the updated by Joshep Stigliz who won noble prize. The adverse selection always happen in insurance industry and capital market.

Advese selection is a consequence result from firm or individual aim at applying some policy toward one group of people but wrongly benefit other groups. Taking a simple example, in banking industry, bank might wish to raise interest rate for business project that are risky to avoid not being pay back but when the bank raise higher interest rate it is only the most risky borrower who come to as for fund from bank. Why? because they already known that such high interes rate they will be unable to pay. In this example, you see bank increase intrest rate policy is target toward all borrower but in the end it is only risky borrower who come to borrow money from bank. Another example, is the insurance in cancer industry, if insurance company wish to increase the premium for those who want to buy insurance against disease such as cancer or operation, then it is only those who is in helpless situation or those who know that they will die soon will buy insurance from the company. Why? Because they know that they will never recover from the disease, thus no need to worry how high is the premium they will buy insurance from the company.

Therefore, the problem of moral harzard and adverse selection originated from imperfect information between economic agents. Then, the solution is to try to creat more information but since information is public goods (non-rival ) then it is the government who should play this role.

My Understanding on Globalization and International Capital Mobilization: The way ahead

What dose the word globalization appeal to you? People might have different view on the meaning of globalization as they come from different background. Economist may regard globalization as a process toward global market, global currency, global free trade, or the internationalization in goods, production, trade, distribution in a way that exchange across border barriers have been removed and transaction cost has been minimzed. Whereas, legal analysist might think globalization is the process toward unique in a legal instrument such as international trade law, international criminal law which is equiped with broader competency to apply on all nations. In the same fashion, a lawyer might refer the globalization as process toward a global institution with international judicial power to execute or punish the illicit crime regardless the occurence of the fact. A sociologist might on his own way beleive globalzation is a process to harminize the different culture, in a peaceful and matual understanding.

Is globalization bad or good for developping country? You might say it is both come with benefit and cost. Thus, the effect of globalization is ambigious depending wheather the magnitute of latter is large enough to cover benefit. It might be impossible to describe the cost and benefit of globalization in a short blog or a couple of pages.However, I am trying to offer some of my own understanding on this topic from viewpoint of liberalization in capital account.

Most developping countries, especially those in Southeast-Easia, including Cambodia, the East Asia or even the former Soviet Union has already experienced the financial crissis. Although different arguments has been suggested as the cause of the crisis, the conclusion tend to converge to a simple one. World Bank, IMF, ADB, as well as most prominent economost such as Stiglitz, Krugman, Baghwati, and many other economist accepted that a quick liberalization of capital account is the cause for most developping countries to fall into the Fiancial crisis in 1997.

What are different view on the Asia Financial Crisis (AFC) in 1997. The IMF and US who strongly tied with Adam Smith of free market economies said the crisis come from internal factor of each developping countries that dose not manage capital market in a transparency and is seriouslly ill with corruption. Lending is offer to project proposed by crony or elite where the result of the investment project is not clearly considered cautiouslly. The critic of IMF said IMF seem to release the responsiblity only on the internal factor and neglect the international factor that bring countries to crisis. Critic added that IMF mentioned this cause just to take chance impossing reform in Southeast Asia and many other developping countries to follow its purpose. The critic against IMF includes WB and some prominent economist such as Stiglizt and Bahagwati. The critic say the crisis is rooted from the IMF itself that forced developping country to liberate its capital market too soon before an enough capacity of each country to deal with the liberalization is achieved.

The crisis is due to the fixed exchange rate system creatd by IMF to facilitate free trade where IMF beleive having a control system of currecny will help to smooth cross border trade. However as each country pegged it currecy to US dollar then when the arbitrager and speculators simultneously prompt for the reserve the central bank is vunerable to reserve exhausted and the crisis will start. This experience is the same as in Argentine, Brazil and Mexico. In Thailand, the capital flight whichi is known as hot money abruptly fly to US seeking for higher interest profit which cause collapse and lose in beliefon Thailand economic stability. This can be said crisis happens because people believe it will just like an inertia inlfation expectation priciple of Irwin Fisher.

In short, we can breifly say that the crisis occur because the countries is too much hurry to open it capital account to liberalization.Therefore, some measure has been prospose by World Bank as well as UNCTAD to control the capital flow. Including, the measurement that all bank and large corporation need to disclose its financial content and financial statement as well as some restrictive measure agiasnt trading on stock market.

Returning to liberalization of capital account, it is unavoidable that a country can close itself or completely prevent capital inflow. Even, the socialist or communist country is now open ther makert for trade. However, country can impose some measure on the flow of capital on an attempt to manage or drive it for its own benefit. In Chilie, there exist some kind of tax on capital flow but not that tax is a form of intervention by government to distort the price on the market and it is not like the direct measurement.

How about Camobodia, open a stock market is a good to raise international capital and mobilize the money under the pillow of most Cambodian but expericne such financial crisis consideration is important.

Therefore, globalization is ahaed and no one can stop it now but we need to manage globalization as Stiglizt say what is important is how we lead the globalization a head.

My understanding about Shadow Price in Economic

Several times, I heard the word shadow price. I remeber hearing this word last time from Yanagi hara sensei. What I did get from his explanation is whenever we talk about shadow price it is not the price of goods or service but it is named shadow price because it is the price of constraint facing by individual who wish to maximize or minimize some objective. Prof. Yanagihara gave a mathematical example of a consumer about maximization of utility with budget contraint where he refere to the so-called Lagrang multiplier of that complicated mathematical model as shadow price. But what is the simple meaning in our daily life?

A simple example, a consumer who wish to buy cloth he is facing some constraint. His objective is to get the best qualities and durable cloth, but his under the constraint of his income and price. Then, given price of the cloth if his income decrease by one dollar what will he choose to buy more, less or no cloth. Or let say if the price of cloth decline then he will buy more cloth because the constraint is less restrictive to him.

In labor market, workers wish to have higher salary so that he can support there life but as wage rise and price also rise then the shadow price is higher because the constraint is even serious for workers to purhcase goods on market.

In short, I can summarize that shadow price is price of the constraint facing consume, firm, government or a country while pursuing some objective.

Foreign Direct Investment, Local Contents Requirement and Profit Taxation

In the paper of Lahiri and Ono, the authors have provided an important notice on the benefit gives rise by Foreign Direct Investment (FDI). The writers try to express the benefit of local contents requirement regulation imposed by host government against foreign investor. The local contents here refere to employment of host country labor.

In reality, we observe the inflow of foreign firm into developing country like Cambodia, seeking for lower labor cost. The local content requirement might not be necessary regarding labor however if we take into account the other kind of input produce or endowed by host country we can realize the opportunity of growth of intermediate supply industry. Host country firm can grows by becoming the main supplier for multinational corporation. This is usaully known as backward linkage. Government of host country should play role in embedding multinational firm within a favorable industry structure that provide this linkage effect.

Returning to Lahiri and Ono paper, I notice a few extreem assumption that should be revise to make the model applicable for developing countries such as Cambodia.

The assumption that input cost in home country is higher than host country
The assumption that ouput or product produce by multinational subsidiary in host country is target for host country market.
In reality, as I said above most FDI tend to seek benefit from different in factor price across countries and also most FDI that came to host country is export oriented-aim at exporting to third country rather than host country market. For example, garment industry in Cambodia is most owned by chinese-owned enterprise which target EU and US market.

However, the conclusion with the two extreme assumption offer a significant insight on the benefit of local content requirement regulation. Mainly the two effect raised by authors that is the unemployment reduction effect and price-lowering effect (Higher consumer surplus). It is true that FDI lead to job creation, mostly in unskilled labor employment. Nevertherless, the price reduction effect is subject to emprical studies whether FDI leads to reduction in monopolistic power or not.

My opinion is that the welfare analysis tool used by author based on price lowering effect in term of Consumer surplus is applicable only in the case large country with high potential market such as China or India but is inappropriate for Cambodia.

The conlcusion is the welfare anlaysis should be enrich by relaxing the two extreem assumption and I think it may give rise for new research to fill this gap.

The detain of paper is Sajal Lahiri and Yoshiyasu Ono (1998) , “Foreign Direct Investment, Local content requirement and Profit taxation”, The Economic Journal, 108, pp. 444-457.

The different between cross-section data and time series data

Cross-section data are the most convinent type of data use by researchers in both economic and non-economics field. It has been used extensively in social science for various purpose such as statistical analysis, prediction and hypothesis test. So what is a cross-section data, and what is time-series data? A simple definition is cross-section data is data we collect during a particular point of time, say in 2007 or in December 2007. Whereas, the time series data consists of data we collected from a contimum of year, usually in an orderly increasing, say from 2000 to 2007.

The most convenient property of cross-section data is randomness. Because of this qualification then each observations in the population is randomly selected. This radomness ensure that cross-section data satisfy the Gauss-Maskov assumption. The Gauss-Maskov assumption is a set of assumption required for econometric regression, called Ordinary Least Square Regression (OLS). The proof and logic for the requirement of these assumption is quite complicated but it is the core of econometric field of study.

Then whenever, the Gauss-Makov assumotion is satistfied we can use any statiscal sofware package to analyze our data. Excel, E-veiw, SPSS, or TSP will meet our objective but preference may depend on users.

Turning to the time series data, it dose not carry the random qualification. As noted by an order sort of data, say from 2000 to 2007 this means randomness is violated, therefore the Gauss-Maskov Assumption is not guarenteed. Nevertheless, some additional assumptions are need to meet the Gauss-Maskov Assumption, such as strict exogenity and no serial corrleation. However when the additonal assumptions meet we can agains do the regression and run our econometric analysis. Agains the prefere software will help us.

There are another type of data, the pooling data and panel data with is a hybrid of cross-section and time-series data. However, the requirement for regression is the same.

The most important thing in Econometric or statistical analysis is Randomness of data.

Foreign Direct Investment and Profit Repatriation

Accorindg to the paper of J. Markusen, he mentioned that FDI will result in welfare improvement for the home country but the welfare for host country is ambiguous. His analysis is basically based on the general equilibrium analysis. The model he has constructed has demonstrated the growth in efficiency for host country and the world, in the model of two country, two goods model.

He mentioned the efficiency of Multi-plant economies created by Muntinational Firm, result from the ability to avoid the duplication of joint-input. To put it simple, he raise a simple example a multinational corporation who decide to centralize the firm specific activities in home country (such as R&D, marketing, advertisement) is able to establish plant in host country while allowing only production activities in host country. By this process, Multinational firm can avoid setting firm specific activities in host country hence benefit from avoiding the duplication of joint input.

Concerning the welfare in home country of the munltinational firm the author has prove that it always ensured but for the case of host country is abitrary. The ambiguous result of multinational firm investment is due to the profit repartriation by multinational firm to home country. Therefore to ensure that the welfare improvement in host country, some kind of measure is needed that is the tax on profit repartriation (non-distortion tax) and the Betrant behavior by new entrant.

The conclusion offers an interesting idea for developping country that seek to attract FDI inflow and always allow free repatriation. This kind of point must taken into account for policy maker. However, FDI may result in other kind of benefit such as technology spillover or employment generation othern than income aspect.

(The detail of the paper is found in Markusen, J.R (1984), “Multinationals, Multi-plant Economies, and the Gains from Trade”, Journal of Internationa Economics, 16, pp. 205-226.)

Market Failure and Government Intervention

In orthodox economics theory, the concept which originated from Adam Smith is Inivisble hand. This invisible hand is nothing but price machanism of market that plays role in allocation of resource in an efficient market. Class school beleive that price is flexible and price adjustmetn will lead to equilibrium, where demand and supply equal one another.

To put it simply, classical economist value that if there is any excess or shortage of demand then price will bid up or down to reflect the nature this inequilibrium. Taking a very simple example of partial market equilibrium such as rice market if demand exceed supply than price will rise, alternatively if supply exceed demand then price will decline. The only motionless point is where supply equal demand.

Do market is always efficent? If it is true then why would still people be unemploy? Those who are willing to work but is not hired by firm. Then this is a critical evident against market failure. Furthure, in stock market where information plays important role, according to Stiglizt is market imperfection is the main cause of market failure.

This kind of failure need government intervention. Government play role to make market effiecient or in some case even market is efficient role of government is important because the role need to redistriubtion of income and ensure equality. The welfare theorem, widely known as Walras’s law mentions about Pareto optimal where not other alternative allocation could be better off without worsen of the others. This law implies the role of government.

Can government fail? True, breaucary, red-tap and corruption than make government policy fail. Then, we must think both of market failure and government failure.