Where does James heckman come from?

James. Heckman is a famous American economist, a professor of economics at the University of Chicago, one of the representatives of Chicago School of Economics, and the winner of the 2000 Nobel Prize in Economics.

Heckman was born in Chicago, Illinois, USA 1944. He studied in the Department of Mathematics of Colorado College and received his Ph.D. in the Department of Economics of Princeton University at 197 1. He has taught at Columbia University, Yale University and University of Chicago. The pioneer of microeconomics, together with Daniel McFadden, won the 2000 Nobel Prize in Economics because of its development and contribution to the principles and methods of analytical selective sampling.

20 18, 1 1 was appointed honorary professor of Peking University University of Economics.

Chinese name: James Heikman

Nationality: USA

Place of birth: Chicago, USA

Date of birth: 1944 04 19.

Occupation: Scholar

Graduate School: Department of Mathematics, Colorado College

Main achievements: the pioneer of microeconomics.

Won the 2000 Nobel Prize in Economics.

Representative works: research on individual econometrics, microeconomics, labor supply and salary determination, etc.

biography

James heckman (1April 1944 19) was born in Chicago, Illinois, USA. He studied in the Department of Mathematics of Colorado College and received his Ph.D. in the Department of Economics of Princeton University at 197 1. He has taught at Columbia University, Yale University and University of Chicago. The pioneer of microeconomics, together with Daniel McFadden, won the 2000 Nobel Prize in Economics because of its development and contribution to the principles and methods of analytical selective sampling.

Since 1995, heckman has been appointed as Professor Henry Schultz of Outstanding Achievement Economics at the University of Chicago. Heckman's research contents in the field of economics involve social project evaluation, econometric model of discontinuous selection and longitudinal data, labor market economics and mode selection of income distribution, etc.

In 2000, the Nobel Prize in Economics was awarded to two American economists, James heckman and Daniel McFadden, in order to reward them for developing theories and methods widely used in the statistical analysis of personal and family behaviors in economics and other social sciences. In particular, heckman was awarded the prize for his "development and contribution to the analysis of selective sampling principles and methods". Mcfadden won the prize for developing the theory and method of analyzing discrete choice. The discipline field that these two economists are engaged in can be called microeconomics. In the early years, econometrics was mainly used in macroeconomics, that is, it mainly studied the economic behavior with the national economy as the main body. Microeconomics, that is, the economic behavior of individuals, families and enterprises; For example, what are the economic factors that determine an individual's choice in education, employment and housing? And what incentives different labor markets and education programs have on personal income and employment. Few people have studied this kind of problem before. One reason is that statistics in this field are hard to find. In the past 30 years, micro-statistical data have become more and more abundant, which provides the possibility for studying micro-econometrics, but there are also many new statistical problems to be solved. For example, the statistical samples of personal or family behavior are not necessarily random, so they are not necessarily representative; Some characteristics that affect personal behavior are unobservable and so on.

Erudition and academic contribution

Research on Individual Econometrics

Heckman and Daniel McFadden, another winner of the 2000 Nobel Prize in Economics, have made great contributions to the establishment and development of individual econometrics and made outstanding contributions to the theory and methods of microeconomics. They have designed analytical methods to study people's lifestyle decisions, which have been widely used in the statistical analysis of individuals, families and enterprises in economics and other social disciplines. These theories and methods are of great practical significance to the study of social and economic problems such as education and training plan, urban transportation system and housing for the elderly. To understand their contribution, we must first understand the individual econometric research. The so-called individual econometrics refers to the quantitative study of the behavior of economic individuals such as families and manufacturers. The research object is very extensive, mainly including labor economics topics: labor supply, wage determination, education choice, unemployment period, immigration, career choice, reproductive choice, gender discrimination, racial discrimination and so on. The theme of public economics: the influence of tax policy and social welfare: the research theme of consumer behavior: commodity demand, brand choice; Theme of urban and transportation economics: housing rental and purchase choice, location choice and transportation choice; Special topics of industrial economics: selection of production forms, demand of production factors, evaluation of production efficiency, etc.

It is worth mentioning that an important reason for the rapid development of econometric research on economic individuals in the past few decades is that a number of large-scale "individual data" databases have appeared during this period. The so-called "individual data" is the data collected by economic individuals such as families and manufacturers, generally in the form of "cross section" (that is, investigating multiple economic individuals at a certain time point), but in recent years, "tracking data" (that is, investigating the same batch of economic individuals at multiple time points) has become more and more popular, and tracking data began at the end of University of Michigan 1960.

The introduction of these large-scale individual databases not only helps to verify the existing economic theories more accurately and rigorously, but also leads to many new econometric topics, mainly focusing on the characteristics of individual data itself. In the process of analyzing and discussing these new topics, econometric methods have also developed by leaps and bounds, and the research on individual econometrics has also grown sturdily with the popularization of individual databases. In addition, due to the popularization of computers and the rapid improvement of computing power, it is feasible to process a large number of individual data, which is also an important reason for the progress of individual econometrics research.

Microeconomic metrology

Simply put, microeconomics is a marginal discipline between economics and statistics, including economic theories and statistical methods used to analyze micro data. That is, the microscopic data reflecting individuals, families and enterprises are analyzed through economic theory and statistical methods, from which more essential economic information reflecting society can be obtained. Microscopic data generally have two forms of expression: one is called cross-sectional data, which is a collection of different situations at the same time; The other is called longitude data, that is, a collection of continuous situations of the same observation unit at different points (such as years). In the past 30 years, the field of microeconomics has been rapidly expanded due to the emergence of large databases including micro-data. At this time, the micro-data is more and more easy to obtain and the computing power is stronger and stronger, which provides brand-new convenience and possibility for the empirical analysis and test of microeconomic theory; On this basis, researchers have the ability to examine and analyze many new problems about "individuals". With the development of econometrics, the application of micro-data has also produced many new statistical problems. Especially because of the inherent limitations of non-experimental data, researchers can usually only observe specific individuals of certain variables, so this non-random sampling sample cannot be representative in the whole population. Even if the sample is representative, it is impossible to observe some characteristics that affect individual behavior, which makes it difficult or even impossible to explain some differences between individuals. James heckman's theory fills these gaps, and he puts forward some solutions to some basic statistical problems related to this kind of micro-data analysis, which promotes the development of econometric theories and methods. The collection of individual data is mostly carried out under the condition of incomplete random sampling, and the reason why sampling is not random is because the observed values of individual data come from economic individuals such as families and manufacturers, and these economic individuals themselves (or other economic individuals around them) have the ability to choose and judge, so it is likely that some actions will be taken to affect sampling, which will make sampling lose randomness and the collected samples cannot accurately represent the matrix. For example, we can only get information about working hours and wages from people who have jobs, but there is always a large proportion of people who have no jobs in the total population. It is impossible for any database to include these people's working hours or wages. No matter how objective and random the sampling process is, the working hours or wages obtained are not strictly representative. If traditional econometric methods are used to analyze such data, any inference can only represent the behavior of workers, but not the behavior description of the whole population. If we still interpret the empirical results as universally applicable findings, we will definitely make a mistake of generalizing, which is the so-called "sample selection error".

Heckman not only made great contributions to the theory of individual econometrics, but also conducted many in-depth empirical studies. He has obtained a wealth of empirical research results, and provided many original opinions on topics such as labor supply, wage determination, unemployment period, benefit evaluation of labor market consultation plan, fertility and gender discrimination.

Labor supply and salary decision

Heckman's analysis of sample selection began with his empirical study of labor supply in the early 1970s. In the field of labor supply, heckman initiated the so-called "second generation" labor supply model, which directly integrated the random interference items necessary for the general measurement model into the process of maximizing the utility of the labor supply side, thus directly deriving the labor supply measurement model. Compared with the traditional labor supply model, this econometric model can describe the "psychological process" of labor suppliers more accurately, and can also be used to analyze two decisions of labor suppliers: whether to work or not and how many hours to work every day. What is more commendable is that the second generation labor supply model solves the problem of sample selection in labor supply data. Heckman put forward the relevant discussion in a paper in 1974. He pointed out that according to the theory of individual economy, whether to work is determined by the process of maximizing the utility of labor suppliers (especially women), and this process can be explained in the following ways: labor suppliers draw up a "reserved salary" according to their own needs, and labor suppliers will only start working after finding a job with a salary greater than this reserved salary. In other words, whether a person works or not depends entirely on the comparison between the reserved salary and the real available salary. This explanation not only describes the decision-making process of labor supply, but also answers the question of why there is a sample selection of labor supply materials. Only by making clear the reasons of the sample selection problem can we put forward a solution, which is exactly the way that heckman handled the sample selection problem step by step based on the theory of individual economy.

Labour market consulting program

Labor market consulting programs, such as on-the-job training, employment assistance and employee allowances, have been implemented in many countries for many years. Evaluating the benefits of these plans is of course a very important issue. Heckman's great contribution to this topic is still pointing out the existence of sample selection: when we try to measure how helpful a labor market consulting project is to participants, we can only compare the differences between participants and non-participants. However, from the previous discussion on sample selection, we should know that every participant in the plan only joins the plan after some evaluation, and only chooses to join if he thinks it is helpful to him. In other words, whether to participate in the plan is by no means random, so there are sample selection problems in the sample data of plan participants and non-participants. To compare the difference between them, we must adopt a measurement and processing method similar to heckman's two-stage method. In a series of follow-up studies, heckman further pointed out that general measurement methods dealing with sample selection problems may not completely eliminate sample selection errors in scheme evaluation. Therefore, he once suggested collecting data through experiments to fundamentally avoid the problem of sample selection, and made a detailed theoretical analysis of this suggestion. Summarizing the research of heckman and other scholars in recent 20 years, it is found that it is impossible for us to evaluate all consulting projects with a single measurement method, and the evaluation of project benefits must be handled on a case-by-case basis. From a large number of cases done in heckman, we can also find that most of the labor market counseling programs are of little help to participants, and different forms of projects will have very different effects on different participants.

duration

The so-called "duration" refers to the duration of an event. The application of econometric analysis of duration in economics includes unemployment duration, strike time, business cycle, consumer shopping time and many demographic topics, such as marriage, childbirth, longevity and migration. Heckman also made considerable contributions to the study of duration, and he paid special attention to the problem of "hidden differences" in duration data. Now take the analysis of unemployment period as an example to illustrate the influence of hidden differences: among the unemployed, the unemployed with better quality are more likely to find new jobs, so their unemployment period is shorter, while the unemployed with relatively poor quality will definitely have a longer unemployment period. Therefore, the difference between "long-term unemployment sample group" and "short-term unemployment sample group" may not be completely random, but belongs to the difference between two different groups with fundamental differences in quality. What is the difference between the two groups is usually not fully confirmed, so these unrecognizable quality differences are called hidden differences. In other words, the difference in unemployment period is probably caused by the hidden difference that cannot be confirmed. If there are too many,

In this discussion, we should see that the influence of hidden differences on duration analysis is similar to that of sample selection, and the processing of sample selection has always been heckman's interest. In order to solve the problem of hidden differences, heckman put forward some measurement methods without mother number, which were widely used by empirical researchers in continuous period. Heckman himself has done a lot of empirical research on the topic of unemployment and fertility.

Sampling problem

Sampling is the basic problem in econometrics, and sampling deviation and self-selection are the most basic problems in microeconomics research. If a sample can't randomly represent its population, sampling deviation may occur. Generally speaking, a sample is either the result of data collection rules or the result of economic man's own behavior. The latter is a process of self-selection. Heckman's breakthrough in self-selection mainly occurred in the mid-1970s. These theoretical breakthroughs are closely related to his painstaking research on individual decisions of labor participation and working hours. When only the working hours of those individuals who choose to work are investigated, they may encounter samples with self-selection problems. In an article published in 1974, heckman designed an econometric method to solve the problem of self-selection when studying the labor supply of married women. This research has become an excellent example of the combination of microeconomic theory and microeconomic method.

Heckman put forward another method to solve the problem of self-selection in his subsequent research work, namely the famous heckman correction method, also known as the two-stage method or heckman method. This method is extremely convenient to apply and has far-reaching influence. Heckman correction method is divided into two steps: first, the researcher designs a model to calculate the individual working probability according to economic theory, and the statistical estimation results of the model can be used to predict the probability of each individual; In the second step, the researchers combined these predicted individual probabilities into an additional explanatory variable to correct the self-selection problem together with variables such as education and age. In this way, the estimated wage relationship is statistically appropriate.

Academic writing

Heckman's main works are: Assessing Welfare Status (co-authored with Smith,1998);

Variable method of correlated random coefficient model (1998);

Measurement and evaluation of social projects (2002);

Estimation of educational income of different groups (2002).