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Journal articles on the topic 'Economics and econometrics'

Author: Grafiati

Published: 4 June 2021

Last updated: 26 July 2025

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1

Thomas, By Jim. "Victor Edelberg: LSE’s forgotten econometrician." Oxford Economic Papers 72, no. 4 (2020): 1006–31. http://dx.doi.org/10.1093/oep/gpaa030.

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Abstract Given Lionel Robbins’s strong scepticism about the value of statistical analysis in economics, it is not surprising that early developments in Econometrics at LSE came from members of the Statistics Department at the School. However, Victor Edelberg, a graduate student in the Economics Department at LSE in the 1930s, published the second article in Econometrica with ‘Econometrics’ in the title and further econometric articles in the Review of Economic Studies. Despite these publications, his work has been forgotten and is not included in the history of econometrics at LSE, nor in the

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Güriş, Selahattin. "Applied Microeconometrics with Health Data." JOURNAL OF APPLIED MICROECONOMETRICS 3, no. 2 (2023): 37–39. http://dx.doi.org/10.53753/jame.2267.

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In this book review, I would like to introduce the book titled “Applied Microeconometrics with Health Data”. Since the book is an econometrics book, we might talk about econometrics first. Econometrics is one of the branches of economics, therefore it covers the methods used especially in the analysis of any topics concerning economics. However, econometric methods can be used in many branches of science such as Health Sciences. First of all, we could assert that econometrics could be used in the economic analysis of events encountered in different branches of science. In addition, econometric

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Hillier, Grant, Raymond Kan, and Xiaolu Wang. "COMPUTATIONALLY EFFICIENT RECURSIONS FOR TOP-ORDER INVARIANT POLYNOMIALS WITH APPLICATIONS." Econometric Theory 25, no. 1 (2009): 211–42. http://dx.doi.org/10.1017/s0266466608090075.

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The top-order zonal polynomials Ck(A), and top-order invariant polynomials Ck1,…,kr (A1, …, Ar) in which each of the partitions of ki, i = 1, …, r, has only one part, occur frequently in multivariate distribution theory, and econometrics — see, for example, Phillips (1980, Econometrica 48, 861–878; 1984, Journal of Econometrics 26, 387–398; 1985, International Economic Review 26, 21–36; 1986, Econometrica 54, 881–896), Hillier (1985, Econometric Theory 1, 53–72; 2001, Econometric Theory 17, 1–28), Hillier and Satchell (1986, Econometric Theory 2, 66–74), and Smith (1989, Journal of Multivariat

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Athey, Susan, and Guido W. Imbens. "Machine Learning Methods That Economists Should Know About." Annual Review of Economics 11, no. 1 (2019): 685–725. http://dx.doi.org/10.1146/annurev-economics-080217-053433.

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We discuss the relevance of the recent machine learning (ML) literature for economics and econometrics. First we discuss the differences in goals, methods, and settings between the ML literature and the traditional econometrics and statistics literatures. Then we discuss some specific methods from the ML literature that we view as important for empirical researchers in economics. These include supervised learning methods for regression and classification, unsupervised learning methods, and matrix completion methods. Finally, we highlight newly developed methods at the intersection of ML and ec

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Zelepukhin, Yuri Valentinovich, and Olga Yurievna Tsybina. "Improvements in the formation of econometric knowledge at training of bachelors - teachers of economic profile." Samara Journal of Science 5, no. 1 (2016): 152–56. http://dx.doi.org/10.17816/snv20161305.

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The concept of modernization of Russian education raises the question about necessity of introduction of profile training to improve and develop the school system of education. It is important that the implementation of ideas to improve education a priority is the presence of expert teachers to work in specialized classes. One of the most difficult is to educate students to work in classrooms socio-economic profile. Future teachers enrolled in the profile "Economics", must use economic, mathematical and econometric methods in solving socio-economic issues, to know the achievements of world eco

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Ditzen, Jan, and Simon Reese. "xtnumfac: A battery of estimators for the number of common factors in time series and panel-data models." Stata Journal: Promoting communications on statistics and Stata 23, no. 2 (2023): 438–54. http://dx.doi.org/10.1177/1536867x231175305.

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In this article, we introduce a new community-contributed command, xtnumfac, for estimating the number of common factors in time-series and panel datasets using the methods of Bai and Ng (2002, Econometrica 70: 191–221), Ahn and Horenstein (2013, Econometrica 81: 1203–1227), Onatski (2010, Review of Economics and Statistics 92: 1004–1016), and Gagliardini, Ossola, and Scaillet (2019, Journal of Econometrics 212: 503–521). Common factors are usually unobserved or unobservable. In time series, they influence all predictors, while in paneldata models, they influence all cross-sectional units at d

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Aradillas-López, Andrés. "The Econometrics of Static Games." Annual Review of Economics 12, no. 1 (2020): 135–65. http://dx.doi.org/10.1146/annurev-economics-081919-113720.

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This article reviews the econometrics of static games, with a focus on discrete-choice cases. These models have been used to study a rich variety of empirical problems, ranging from labor force participation to entry decisions. We outline the components of a general game and describe the problem of doing robust inference in the presence of multiple solutions, as well as the different econometric approaches that have been applied to tackle this problem. We then describe the specific challenges that arise in different variations of these models depending on whether players are assumed to have co

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Hozer, Józef, and Mariusz Doszyń. "Econometric Models of Propensities." Folia Oeconomica Stetinensia 6, no. 1 (2007): 15–25. http://dx.doi.org/10.2478/v10031-007-0008-1.

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Econometric Models of Propensities Human being is one of the most important sources of causative forces of events that assemble economical processes. Working out the effective tools that enable measurement of the impact of people on socio-economic processes is necessary in analyzing, troubleshooting and forecasting. In the article the issues of calculating propensities by means of properly specified econometrics models were presented. The definition of propensity was introduced. Questions connected with topic of propensities were presented in context of concepts promoted by Szczecin school of

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9

Haug, Alfred A. "TESTING LINEAR RESTRICTIONS ON COINTEGRATING VECTORS: SIZES AND POWERS OF WALD AND LIKELIHOOD RATIO TESTS IN FINITE SAMPLES." Econometric Theory 18, no. 2 (2002): 505–24. http://dx.doi.org/10.1017/s0266466602182119.

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The Wald test for linear restrictions on cointegrating vectors is compared in finite samples using the Monte Carlo method. The Wald test is calculated within the vector error-correction based estimation methods of Bewley, Orden, Yang, and Fisher (1994, Journal of Econometrics 64, 3–27) and of Johansen (1991, Econometrica 59, 1551–1580), the canonical cointegration method of Park (1992, Econometrica 60, 119–143), the dynamic ordinary least squares method of Phillips and Loretan (1991, Review of Economic Studies 58, 407–436), Saikkonen (1991, Econometric Theory 7, 1–21), and Stock and Watson (19

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Jakimowicz, Aleksander. "The Role of Entropy in the Development of Economics." Entropy 22, no. 4 (2020): 452. http://dx.doi.org/10.3390/e22040452.

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The aim of this paper is to examine the role of thermodynamics, and in particular, entropy, for the development of economics within the last 150 years. The use of entropy has not only led to a significant increase in economic knowledge, but also to the emergence of such scientific disciplines as econophysics, complexity economics and quantum economics. Nowadays, an interesting phenomenon can be observed; namely, that rapid progress in economics is being made outside the mainstream. The first significant achievement was the emergence of entropy economics in the early 1970s, which introduced the

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11

Martin, Vance L. "Econometric Society Australasian Meetings 1997 (ESAM97)." Econometric Theory 14, no. 6 (1998): 800–801. http://dx.doi.org/10.1017/s0266466698146066.

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The Econometric Society Australasian Meeting in 1997 was hosted by the economics department at the University of Melbourne on July 2 to 4 with Peter Bardsley (economics) and Vance L. Martin (econometrics) as cochairpersons. Special features consisted of a star-studded lineup of invited speakers, the inaugural E.J. Hannan lecture, a range of special seminars in economic theory and econometric theory, and a number of nonacademic but spirited special events that took place both during and after the conference.

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Burbank, Irvin K. "Mathematics + economics = econometrics." International Journal of Mathematical Education in Science and Technology 19, no. 5 (1988): 723–27. http://dx.doi.org/10.1080/0020739880190510.

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Keynes, J. M. "Professor Tinbergen’s Method." Voprosy Ekonomiki, no. 4 (April 20, 2007): 37–45. http://dx.doi.org/10.32609/0042-8736-2007-4-37-45.

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The article written by the classic of economic science in 1939, which is published in Russian for the first time, contains a critique of the application of econometric methods in economics. The object of criticism is one of the first large-scale econometric studies - the book by J. Tinbergen on business cycles. Keynes points at the arbitrariness of many econometric judgments, at the problems of causality and forecast in econometrics. He also mentions that a lot of economic problems cannot be analyzed by means of econometric technique.

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de Paula, Áureo. "Econometric Models of Network Formation." Annual Review of Economics 12, no. 1 (2020): 775–99. http://dx.doi.org/10.1146/annurev-economics-093019-113859.

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This article provides a selective review of the recent literature on econometric models of network formation. I start with a brief exposition on basic concepts and tools for the statistical description of networks; then I offer a review of dyadic models, focusing on statistical models on pairs of nodes, and I describe several developments of interest to the econometrics literature. I also present a discussion of nondyadic models in which link formation might be influenced by the presence or absence of additional links, which themselves are subject to similar influences. This argument is relate

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Siddique, Muhammad Zahid. "Can Econometrics Rescue “The Economics”?" NUST Journal of Social Sciences and Humanities 2, no. 1 (2021): 51–76. http://dx.doi.org/10.51732/njssh.v2i1.8.

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Economists disagree; this is a matter of fact. Economics has an empirical methodology to verify whatever theories economists from different schools of thought advance in order to explain the economic phenomenon. This empirical methodology lends economists the confidence that most of the differences among them can be reconciled overtime by employing this methodology. If not today, future development either in economic theorization or estimation techniques may help them settle their internal conflicts. This paper argues that disagreements among economists are deeper than they are usually conceiv

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Fan, Yanqin, and Andrew J. Patton. "Copulas in Econometrics." Annual Review of Economics 6, no. 1 (2014): 179–200. http://dx.doi.org/10.1146/annurev-economics-080213-041221.

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17

Morck, Randall, and Bernard Yeung. "Economics, History, and Causation." Business History Review 85, no. 1 (2011): 39–63. http://dx.doi.org/10.1017/s000768051100002x.

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Economics and history both strive to understand causation: economics by using instrumental variables econometrics, and history by weighing the plausibility of alternative narratives. Instrumental variables can lose value with repeated use because of an econometric tragedy of the commons: each successful use of an instrument creates an additional latent variable problem for all other uses of that instrument. Economists should therefore consider historians' approach to inferring causality from detailed context, the plausibility of alternative narratives, external consistency, and recognition tha

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Horowitz, Joel L. "Bootstrap Methods in Econometrics." Annual Review of Economics 11, no. 1 (2019): 193–224. http://dx.doi.org/10.1146/annurev-economics-080218-025651.

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The bootstrap is a method for estimating the distribution of an estimator or test statistic by resampling one's data or a model estimated from the data. Under conditions that hold in a wide variety of econometric applications, the bootstrap provides approximations to distributions of statistics, coverage probabilities of confidence intervals, and rejection probabilities of hypothesis tests that are more accurate than the approximations of first-order asymptotic distribution theory. The reductions in the differences between true and nominal coverage or rejection probabilities can be very large.

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19

Magnus, Jan R., and Mary S. Morgan. "The ET Interview: Professor J. Tinbergen." Econometric Theory 3, no. 1 (1987): 117–42. http://dx.doi.org/10.1017/s0266466600004151.

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Jan Tinbergen is one of the founding fathers of econometrics, publishing in the field from 1927 until the early 1950s. This was the frontier age of econometrics when the distinction between mathematical economics and econometrics, let alone between theoretical and applied econometrics, did not yet exist. Tinbergen's approach to economics has always been a practical one. This was highly appropriate for the new field of econometrics, and enabled him to make important contributions to conceptual and theoretical issues, but always in the context of a relevant economic problem. The development of t

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Bernardi, Mauro, Stefano Grassi, and Francesco Ravazzolo. "Bayesian Econometrics." Journal of Risk and Financial Management 13, no. 11 (2020): 257. http://dx.doi.org/10.3390/jrfm13110257.

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The computational revolution in simulation techniques has shown to become a key ingredient in the field of Bayesian econometrics and opened new possibilities to study complex economic and financial phenomena. Applications include risk measurement, forecasting, assessment of policy effectiveness in macro, finance, marketing and monetary economics.

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21

Wickens, Michael, David F. Hendry, and Kenneth F. Wallis. "Econometrics and Quantitative Economics." Economic Journal 95, no. 379 (1985): 791. http://dx.doi.org/10.2307/2233045.

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22

Heckman, James J. "Econometrics and empirical economics." Journal of Econometrics 100, no. 1 (2001): 3–5. http://dx.doi.org/10.1016/s0304-4076(00)00044-0.

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23

Baltagi, Badi H., David F. Hendry, and Kenneth F. Wallis. "Econometrics and Quantitative Economics." Journal of the American Statistical Association 81, no. 395 (1986): 868. http://dx.doi.org/10.2307/2289039.

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24

Jones, Andrew. "Econometrics and health economics." Health Economics 2, no. 2 (1993): 85–86. http://dx.doi.org/10.1002/hec.4730020202.

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Chen, Shu-Heng, Chia-Ling Chang, and Ye-Rong Du. "Agent-based economic models and econometrics." Knowledge Engineering Review 27, no. 2 (2012): 187–219. http://dx.doi.org/10.1017/s0269888912000136.

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AbstractThis paper reviews the development of agent-based (computational) economics (ACE) from an econometrics viewpoint. The review comprises three stages, characterizing the past, the present, and the future of this development. The first two stages can be interpreted as an attempt to build the econometric foundation of ACE, and, through that, enrich its empirical content. The second stage may then invoke a reverse reflection on the possible agent-based foundation of econometrics. While ACE modeling has been applied to different branches of economics, the one, and probably the only one, whic

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Rancan, Antonella. "Econometric modelling in Italy: From economic planning to academic research." HISTORY OF ECONOMIC THOUGHT AND POLICY, no. 1 (November 2021): 63–82. http://dx.doi.org/10.3280/spe2021-001003.

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The paper deals with the introduction and acceptance of econometric model-ling as a tool to conduct economic policy analysis in Italy in the Post War. A re-search practice first applied in public and private institutions other than universi-ties. It is argued that economic planning and policymakers' needs of empirical es-timations, simulations and forecasts played an important role in supporting quan-titative research, at the time when economics was still conceived as a theoretical discipline. Sylos Labini's (1967) econometric model, the Modellaccio (1970-75), the University of Bologna model (

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27

Chung, Joseph H. "Introduction." L'Actualité économique 51, no. 4 (2009): 505–9. http://dx.doi.org/10.7202/800641ar.

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Abstract One of the most significant post-war development in economics has been the contribution of econometrics to the refinement of techniques of analysis. Econometrics is now an integral part of economics teaching in most of the known universities throughout the world and large econometric models are being used for economic policies in industrialized countries. The CANDIDE model (Canadian Disaggregated Inter-Departmental Econometric Model) is a medium-term policy oriented model and an indication of some degree of maturity in the Art of model building in CANADA. The purpose of this special i

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Maziarz, Mariusz. "‘Emerging contrary result’ phenomenon and scientific realism." Panoeconomicus, no. 00 (2020): 24. http://dx.doi.org/10.2298/pan171218024m.

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The article is aimed at reconsidering the question if the project of econometrics can be read in line with scientific realism. Previously, the methodological literature focused on the philosophy of econometrics, voices criticizing realist interpretations of econometrics were raised. The criticism was aimed at showing that econometric models lack robustness. The use of slightly different methods leads to obtaining different and often contrary models what supposedly undermine the project of econometrics. In this article, I aim at offering a new argument in defence of the current practice of the

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Keuzenkamp, Hugo A. "THE ECONOMETRICS OF THE HOLY GRAIL ? A REVIEW OF ECONOMETRICS: ALCHEMY OR SCIENCE? ESSAYS IN ECONOMETRIC METHODOLOGY." Journal of Economic Surveys 9, no. 2 (1995): 233–48. http://dx.doi.org/10.1111/j.1467-6419.1995.tb00115.x.

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Chen, Wenhui. "Discussion on Collaborative Teaching of Econometrics in the Field of Environmental Economics." Journal of Contemporary Educational Research 7, no. 11 (2023): 154–59. http://dx.doi.org/10.26689/jcer.v7i11.5590.

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To capitalize on the synergies between the Econometrics course and the Environmental Economics major, this paper aims to enhance students’ability to conduct empirical analysis and practical application using econometric models. It also seeks to promote collaborative teaching through case studies and model research. The primary focus is on the hot research issues within the field of environmental economics, utilizing the econometric model as a vehicle for instruction. To achieve this, the paper proposes the development of a comprehensive case library specific to environmental economics. This re

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QIN, Duo. "BAYESIAN ECONOMETRICS: The First Twenty Years." Econometric Theory 12, no. 3 (1996): 500–516. http://dx.doi.org/10.1017/s0266466600006836.

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This paper sketches the history of how Bayesian inference was adopted and utilized in econometrics during its first 20 years. It focuses on the causes of the Bayesian movement, the ways in which Bayesian inference was applied, the problems that the application was intended to solve, and the results achieved. It shows that Bayesian research has largely followed mainstream econometric development as far as the major econometric ideas and methods are concerned and that Bayesian reformulation of mainstream econometrics has nevertheless helped in deepening econometricians' understanding of many mod

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Cribari-Neto, Francisco, Mark J. Jensen, and Álvaro A. Novo. "RESEARCH IN ECONOMETRIC THEORY: QUANTITATIVE AND QUALITATIVE PRODUCTIVITY RANKINGS." Econometric Theory 15, no. 5 (1999): 719–52. http://dx.doi.org/10.1017/s0266466699155051.

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We rank institutions and researchers based on a standardized page count of their econometric theory publications over the last 11 years (1986–1996) in 11 economics and statistics journals. Our ranking criteria differ from those employed by Hall (1987, Econometric Theory 3, 171–194; 1990, Econometric Theory 6, 1–16) and Baltagi (1998, Econometric Theory 14, 1–43). We weight the standardized page count of a publication by the publishing journal's “impact factor,” which measures a journal's impact on the profession. We also depart from the previous rankings by focusing only on publications in the

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Jaunzems, Andrejs, and Ilze Balode. "The Correctness Problems in Applying Inductive Statistics in Economics and Agriculture." Rural Sustainability Research 37, no. 332 (2017): 20–28. http://dx.doi.org/10.1515/plua-2017-0003.

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Abstract In the article “Professor Tinbergen’s Method” (Keynes J. M. Professor Tinbergen’s Method. − The Economic Journal. 1939. Vol. 49. No. 195) John Maynard Keynes expressed critical notes concerning insufficient scientific level of the Jan Tinbergen’s results obtained with the help of econometric methods. The conclusion of present research is that the critical appraisal of econometric applying given by John Maynard Keynes in 1939 can be completely assigned to many published in Latvia research in economics and business done by inductive statistics because scientists carelessly apply the lin

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Stock, James H., and Mark W. Watson. "Twenty Years of Time Series Econometrics in Ten Pictures." Journal of Economic Perspectives 31, no. 2 (2017): 59–86. http://dx.doi.org/10.1257/jep.31.2.59.

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This review tells the story of the past 20 years of time series econometrics through ten pictures. These pictures illustrate six broad areas of progress in time series econometrics: estimation of dynamic causal effects; estimation of dynamic structural models with optimizing agents (specifically, dynamic stochastic equilibrium models); methods for exploiting information in “big data” that are specialized to economic time series; improved methods for forecasting and for monitoring the economy; tools for modeling time variation in economic relationships; and improved methods for statistical infe

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Domínguez, Manuel A., and Ignacio N. Lobato. "A SIMPLE OMNIBUS OVERIDENTIFICATION SPECIFICATION TEST FOR TIME SERIES ECONOMETRIC MODELS." Econometric Theory 31, no. 4 (2014): 891–910. http://dx.doi.org/10.1017/s0266466614000644.

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Despite their theoretical advantages, Integrated Conditional Moment (ICM) specification tests are not commonly employed in the econometrics practice. An important reason is that the employed test statistics are nonpivotal, and so critical values are not readily available. This article proposes an omnibus test in the spirit of the ICM tests of Bierens and Ploberger (1997, Econometrica 65, 1129–1151) where the test statistic is based on the minimized value of a quadratic function of the residuals of time series econometric models. The proposed test falls under the category of overidentification

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Chetverikov, Denis, Andres Santos, and Azeem M. Shaikh. "The Econometrics of Shape Restrictions." Annual Review of Economics 10, no. 1 (2018): 31–63. http://dx.doi.org/10.1146/annurev-economics-080217-053417.

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We review recent developments in the econometrics of shape restrictions and their role in applied work. Our objectives are threefold. First, we aim to emphasize the diversity of applications in which shape restrictions have played a fruitful role. Second, we intend to provide practitioners with an intuitive understanding of how shape restrictions impact the distribution of estimators and test statistics. Third, we aim to provide an overview of new advances in the theory of estimation and inference under shape restrictions. Throughout the review, we outline open questions and interesting direct

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Chamberlain, Gary. "Robust Decision Theory and Econometrics." Annual Review of Economics 12, no. 1 (2020): 239–71. http://dx.doi.org/10.1146/annurev-economics-081919-042544.

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This review uses the empirical analysis of portfolio choice to illustrate econometric issues that arise in decision problems. Subjective expected utility (SEU) can provide normative guidance to an investor making a portfolio choice. The investor, however, may have doubts on the specification of the distribution and may seek a decision theory that is less sensitive to the specification. I consider three such theories: maxmin expected utility, variational preferences (including multiplier and divergence preferences and the associated constraint preferences), and smooth ambiguity preferences. I u

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Stevens, Guy V. G. "Economics, econometrics and the LINK." International Journal of Forecasting 12, no. 4 (1996): 562–64. http://dx.doi.org/10.1016/s0169-2070(96)00705-4.

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Brauers, Willem K. "Interpreting mathematical economics and econometrics." Long Range Planning 19, no. 1 (1986): 131. http://dx.doi.org/10.1016/0024-6301(86)90141-x.

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Morgan, Mary S. "Perspectives in the History of Econometrics: A Review Essay of R. J. Epstein: A History of Econometrics." Econometric Theory 6, no. 2 (1990): 151–64. http://dx.doi.org/10.1017/s0266466600005090.

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Only in the last few years has the history of econometrics become established as an accepted field of research, with its own doctoral students and sessions at professional meetings. Yet, the first written histories of econometrics appeared as far back as the 1950s, when Carl Christ [4] reviewed the first 20 years' econometric work of the Cowles Commission and George Stigler [37] surveyed the early econometric analyses of consumer demand. Contributions in the intervening years have been sparse, with historical accounts such as Stigler [38], Humphrey [23], and Cargill [3] providing helpful landm

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Mosconi, Rocco, and Paolo Paruolo. "A Conversation with Søren Johansen." Econometrics 10, no. 2 (2022): 21. http://dx.doi.org/10.3390/econometrics10020021.

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This article was prepared for the Special Issue “Celebrated Econometricians: Katarina Juselius and Søren Johansen” of Econometrics. It is based on material recorded on 30 October 2018 in Copenhagen. It explores Søren Johansen’s research, and discusses inter alia the following issues: estimation and inference for nonstationary time series of the I(1), I(2) and fractional cointegration types; survival analysis; statistical modelling; likelihood; econometric methodology; the teaching and practice of Statistics and Econometrics.

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Zhao, Yue, Wenshuai Liu, Yan Yan, and Feiyi Li. "Navigating the confluence of econometrics and data science: Implications for economic analysis and policy." Theoretical and Natural Science 38, no. 1 (2024): 26–31. http://dx.doi.org/10.54254/2753-8818/38/20240551.

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This paper explores the transformative integration of econometrics and data science, a synergy poised to redefine empirical research within economics. By merging traditional econometric methods with advanced data science techniques, such as machine learning algorithms and big data analytics, this interdisciplinary approach enables a deeper, more nuanced understanding of complex economic phenomena. We delve into the theoretical foundations underlying this integration, highlighting how machine learning algorithms like random forests and neural networks complement conventional regression analysis

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Kartaev, Ph S. "How to teach Econometrics to Economists: Bachelor level ..... 72 Macroeconomic Policy." Scientific Research of Faculty of Economics. Electronic Journal 11, no. 2 (2019): 72–90. http://dx.doi.org/10.38050/2078-3809-2019-11-2-72-90.

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The article analyzes approaches to the teaching of econometric subjects of economists. The article describes the teaching experience gained at the faculty of Economics of Moscow state University. Recommendations on the choice of topics and the sequence of their presentation in the framework of the basic course of econometrics; methodology of their presentation; the choice of activities for students to help them master econometrics (both within the basic course and beyond) are formulated.

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Cunningham, Rosemary Thomas. "Economics: Spreadsheets as Pedagogical Tools for Economic Statistics and Econometrics." Social Science Computer Review 12, no. 4 (1994): 493–514. http://dx.doi.org/10.1177/089443939401200403.

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Perrigne, Isabelle, and Quang Vuong. "Econometrics of Auctions and Nonlinear Pricing." Annual Review of Economics 11, no. 1 (2019): 27–54. http://dx.doi.org/10.1146/annurev-economics-080218-025702.

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This review surveys the growing literature on the econometrics of first-price sealed-bid auctions and nonlinear pricing. The complexity of the economic models has initiated fruitful collaborations between econometrics and empirical research. We review the benchmark models and their extensions, the identification of the model primitives, and their nonparametric and semiparametric estimation. We discuss the future of the field, which goes beyond auctions and nonlinear pricing, as both can be viewed as economic mechanisms for price formation, allocation, and market organization.

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Пастушенко, С. Б., and В. В. Реймер. "Econometrics as an integral part of economic sciences." Экономика и предпринимательство, no. 2(115) (May 6, 2020): 1259–63. http://dx.doi.org/10.34925/eip.2020.115.2.253.

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В статье рассматривается роль эконометрики в системе экономических наук. Эконометрика является экономической наукой и неотъемлемой частью экономической теории и экономики, наряду с макро-и микроэкономикой. Эконометрика формирует методологию оценки параметров моделей микро-, мезо-и макроэкономики, а также прогнозирования отдельных экономических процессов на уровне национальной и мировой экономики и на уровне отдельных предприятий. The article discusses the role of econometrics in the system of economic sciences. Econometrics is an economic science and an integral part of economic theory and eco

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Hoover, Kevin D. "On the Reception of Haavelmo’s Econometric Thought." Journal of the History of Economic Thought 36, no. 1 (2014): 45–65. http://dx.doi.org/10.1017/s1053837214000029.

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The significance of Haavelmo’s “The Probability Approach in Econometrics” (1944), the foundational document of modern econometrics, has been interpreted in widely different ways. Some regard it as a blueprint for a provocative (but ultimately unsuccessful) program dominated by the need for a priori theoretical identification of econometric models. Others focus more on statistical adequacy than on theoretical identification. They see its deepest insights as unduly neglected. The present article uses bibliometric techniques and a close reading of econometrics articles and textbooks to trace the

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Harvey, A. C., and Gregory C. Chow. "Econometrics." Economica 52, no. 206 (1985): 276. http://dx.doi.org/10.2307/2554438.

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Angrist, Joshua D., and Jörn-Steffen Pischke. "Undergraduate Econometrics Instruction: Through Our Classes, Darkly." Journal of Economic Perspectives 31, no. 2 (2017): 125–44. http://dx.doi.org/10.1257/jep.31.2.125.

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The past half-century has seen economic research become increasingly empirical, while the nature of empirical economic research has also changed. In the 1960s and 1970s, an empirical economist's typical mission was to “explain” economic variables like wages or GDP growth. Applied econometrics has since evolved to prioritize the estimation of specific causal effects and empirical policy analysis over general models of outcome determination. Yet econometric instruction remains mostly abstract, focusing on the search for “true models” and technical concerns associated with classical regression as

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Molchanov, Ilya, and Francesca Molinari. "Applications of Random Set Theory in Econometrics." Annual Review of Economics 6, no. 1 (2014): 229–51. http://dx.doi.org/10.1146/annurev-economics-080213-041205.

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