The Role of Econometrics Data Analysis Method in the Social Sciences (Education) Research (original) (raw)
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Econometric Methods for Research in Education
2010
This paper reviews some of the econometric methods that have been used in the economics of education. The focus is on understanding how the assumptions made to justify and implement such methods relate to the underlying economic model and the interpretation of the results. We start by considering the estimation of the returns to education both within the context of a dynamic discrete choice model inspired by Willis and Rosen (1979) and in the context of the Mincer model. We discuss the relationship between the econometric assumptions and economic behaviour. We then discuss methods that have been used in the context of assessing the impact of education quality, the teacher contribution to pupils' achievement and the effect of school quality on housing prices. In the process we also provide a summary of some of the main results in this literature.
Journal of Socio-economics, 2011
Econometrics is seen as the dominant method in terms of applicability, accuracy and efficiency in economic science. It is widely used and other methods have been reduced to marginal contributions. Econometricians behave as if their techniques were universal when in fact they are not. If alternative methods are accepted, one can largely eliminate the restrictions and distance to reality of econometrics. The article debates the pathways for a satisfactory economics in a context where theoretical and methodological pluralism is entering even in mainstream ideas. The historical construction of econometrics as the main method in economics and the limitations and possibilities of this tool are explored, underlining the need of pluralism.► This article debates the role of econometrics in economic science. ► The establishment of econometrics as a dominant technique in economics is explained. ► Central assumptions of the method are discussed. ► Opinions of several authors regarding methodological formalism are debated. ► Conclusions underline the need of pluralism to analyze economy today.
NBER WORKING PAPER SERIES ECONOMETRIC METHODS FOR RESEARCH IN EDUCATION
This paper reviews some of the econometric methods that have been used in the economics of education. The focus is on understanding how the assumptions made to justify and implement such methods relate to the underlying economic model and the interpretation of the results. We start by considering the estimation of the returns to education both within the context of a dynamic discrete choice model inspired by and in the context of the Mincer model. We discuss the relationship between the econometric assumptions and economic behaviour. We then discuss methods that have been used in the context of assessing the impact of education quality, the teacher contribution to pupils' achievement and the effect of school quality on housing prices. In the process we also provide a summary of some of the main results in this literature.
Essays in Applied Econometrics and Education
2014
This dissertation consists of three essays. First, we explore the implications of correlations that do not vanishing for units in different clusters for the actual and estimated precision of least squares estimators. Our main theoretical result is that with equal-sized clusters, if the covariate of interest is randomly assigned at the cluster level, only accounting for nonzero covariances at the cluster level, and ignoring correlations between clusters as well as differences in within-cluster correlations, leads to valid confidence intervals. Next, we examine the choice of pairs in matched pair randomized experiments. We show that stratifying on the conditional expectation of the outcome given baseline variables is optimal in matched-pair randomized experiments. Last, we measure the effect of decreased course availability on grades, degree attainment, and transfer to four-year colleges using a regression discontinuity from course enrollment queues due to oversubscribed courses. We f...
Econometrics: an historical guide for the uninitiated
Interdisciplinary Science Reviews, 2013
This essay was written to accompany a lecture to beginning students of the course of Economic Analytics, which is taught in the Institute of Econometrics of the University of Lodz in Poland. It provides, within a few pages, a broad historical account the development of econometrics. It begins by describing the origin of regression analysis and it concludes with an account of cointegration analysis. The purpose of the essay is to provide a context in which the students can locate various aspects of econometric analysis. A distinction must be made between the means by which new ideas were propagated and the manner and the circumstances in which they have originated. This account is concerned primarily with the propagation of the ideas.
This course builds and expands on the knowledge acquired in Econometrics I. As such, it emphasizes both the theoretical and the practical aspects of statistical analysis, focusing on techniques for estimating econometric models of various kinds and for conducting tests of hypotheses of interest to economists. It is designed in such a way so as to help the individual to develop a solid theoretical background in introductory level econometrics, the ability to implement the techniques and to critique empirical studies in economics. 11. Aim of the Course The aim of this course is to provide the basic knowledge of econometrics that is essential equipment for any serious economist or social scientist, to a level where the participant would be competent to continue with the study of the subject in a graduate programme. While the course is ambitious in terms of its coverage of technical topics, equal importance is attached to the development of an intuitive understanding of the material that will allow these skills to be utilised effectively and creatively, and to give participants the foundation for understanding specialized applications through self-study with confidence when needed.
Abdella Mohammed Ahmed (M.Sc.), 2024
What is econometrics? • Literally speaking, the word ‘econometrics’ means measurement in economics. • In general, econometrics is the application of statistical and mathematical methods to the analysis of economic data with a purpose of giving empirical content to economic theories and verifying or refuting them. • More specifically, it is concerned with the use of statistical methods to attach numerical values to the parameters of economic models and also with the use of these models for prediction. • The techniques of econometrics consist of a blend of economic theory, mathematical modelling and statistical analysis. Before any statistical analysis with economic data is performed, one needs a clear mathematical formulation of the relevant economic theory. For example, saying that the demand curve is downward sloping is not enough. We have to write the statement in mathematical form as: q = a + b p, b < 0 or , b < 0 Where q is the quantity demanded and p is the price. One major problem: economic theory is rarely informative about functional forms. Thus, we have to use statistical methods to choose the functional form as well. Putting it differently, we are often presented with no more than the data themselves and the theory behind the data generation process is non-existent or far from being complete. Thus, what we do in practice is: • Investigate the important features of the observed data • Construct an empirical model (incorporating as much available background theory as possible) • Check that the constructed model is capable of capturing these important features The model construction phase is facilitated by specifying a fairly wide class of models within which some optimal search technique may then be applied. The main aim of this course is to provide a good understanding of the properties of linear econometric models and techniques. Although some features of macroeconomic time series cannot be adequately described and analysed using linear techniques, much econometric model building is dominated by linear models. The reasons include: • The theory of statistical inference is most developed for linear models. • Linear approximations to economic relationships have been quite successful in empirical work. Economic and econometric models The first task an econometrician faces is that of formulating an econometric model. What is a model? A model is a simplified representation of a real-world process. For instance, ‘the demand for oranges depends on the price of oranges’ is a simplified representation since there are a host of other variables that one can think of that determine the demand for oranges. These include: • Income of consumers • An increase in diet consciousness (e.g. drinking coffee causes cancer; so better switch to orange juice) • Increase or decrease in the price of substitutes (e.g. that of apple) However, there is no end to this stream of other variables! Many have argued in favour of simplicity since simple models are easier: • To understand • To communicate • To test empirically with data The choice of a simple model to explain complex real-world phenomena leads to two criticisms: • The model is oversimplified • The assumptions are unrealistic For instance, to say that the demand for oranges depends on only the price of oranges is both an oversimplification and an unrealistic assumption. • To the criticism of oversimplification, many have argued that it is better to start with a Simplified model and progressively construct more complicated models. • As to the criticism of unrealistic assumptions, the relevant question is whether they are sufficiently good approximations for the purpose at hand or not. In practice we include in our model: • Variables that we think are relevant for our purpose. • A ‘disturbance’ or ‘error’ term which accounts for variables that are omitted as well as all unforeseen forces. This brings us to the distinction between an economic model and econometric model. An economic model is a set of assumptions that approximately describes the behaviour of an economy (or a sector of an economy). An econometric model consists of the following: a) A set of behavioural equations derived from the economic model. These equations involve some observed variables and some ‘disturbances’. b) A statement of whether there are errors of observation in the observed variables. c) A specification of the probability distribution of the ‘disturbances ‘. With these specifications, we can proceed to test the empirical validity of the economic model and use it to make forecasts or use it in policy analysis. Methodology of econometric research The aims of econometrics are: a) Formulation of econometric models, that is, formulation of economic models in an empirically testable form (specification aspect). b) Estimation and testing of these models with observed data (inference aspect). c) Use of these models for prediction and policy purpose.
A Systems Theoretic Analysis of the Quantitative Interplay Between Econometrics and Education
Income/expenditures, individual expenditures such as education, and performance in schools all relate to systems with defined inputs and outputs and have been formally modeled in accordance with a systems theoretic approach. The Engel’s curves of expenditures on commodities from the Indian National Sample Survey Organization data was hyperbolic limited by a perceived ‘time constant’ associated with commodities while the preferences themselves are ordered hierarchically. School participation (dropouts) as a function of parental income based on available Brazilian data also shows a hierarchical hyperbolic relationship, thereby proving the nature of hierarchy in a naturally ordinal commodity - education. Since the socio-economic influences skew school performance in year-end examinations that demand cramming, retention over the years was tested in a school with a small cross section of 9th grade students uniformly distributed for their previous year’s school grades. The startling findi...