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MiMo SIGNED

Inference in Microeconometric Models

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EC-Contrib. €

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Project "MiMo" data sheet

The following table provides information about the project.

Coordinator
THE CHANCELLOR MASTERS AND SCHOLARSOF THE UNIVERSITY OF CAMBRIDGE 

Organization address
address: TRINITY LANE THE OLD SCHOOLS
city: CAMBRIDGE
postcode: CB2 1TN
website: www.cam.ac.uk

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country United Kingdom [UK]
 Total cost 1˙294˙739 €
 EC max contribution 1˙294˙739 € (100%)
 Programme 1. H2020-EU.1.1. (EXCELLENT SCIENCE - European Research Council (ERC))
 Code Call ERC-2016-STG
 Funding Scheme ERC-STG
 Starting year 2017
 Duration (year-month-day) from 2017-01-01   to  2021-12-31

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    THE CHANCELLOR MASTERS AND SCHOLARSOF THE UNIVERSITY OF CAMBRIDGE UK (CAMBRIDGE) coordinator 1˙192˙696.00
2    FONDATION NATIONALE DES SCIENCES POLITIQUES FR (PARIS) participant 102˙042.00

Map

 Project objective

Unobserved differences between economic agents are an important driver behind the differences in their economic outcomes such as schooling decisions, wages, and employment durations. Allowing for such unobserved heterogeneity in economic modeling equips the specification with an additional dimension of realism but presents major challenges for econometric practice. Hence, reconciling heterogeneity in the data with econometric models is an issue of utmost importance.

The aim of this project is to develop inference methods for models with unobserved heterogeneity by exploiting the identifying power of longitudinal (panel) data. The project consists of three blocks. Together, they span the largest part of modern applications of panel data.

The first block deals with inference on nonlinear models and enhances the performance of statistical hypothesis tests. So far, the literature has focused on point estimation. However, it is statistical inference that accounts for uncertainty in the data and forms the basis for testing economic restrictions. The second block makes progress on the estimation of models for network data. The importance of social and economic connections is well established but few formal results are available. We exploit the fact that network data can be seen as a type of panel data to derive such results. The third block uses panel data to non-parametrically estimate dynamic discrete-choice models with unobserved type heterogeneity and/or latent state variables. Such results are inexistent even though dynamic discrete-choice models are a workhorse tool in labor economics and industrial organization.

The performance of the tools will be assessed theoretically and via simulation, and they will be applied to various empirical problems. Two examples of applications that we will study are the extensive margin of labor force participation and the determinants of the import and export behavior of firms and countries.

 Publications

year authors and title journal last update
List of publications.
2019 Koen Jochmans Vincenzo Verardi
XTSERIALPM: A portmanteau test for serial correlation in a linear panel model
published pages: , ISSN: , DOI: 10.17863/cam.40108
Cambridge Working Papers in Economics 1944 2020-01-23
2019 Jochmans, Koen
Heteroskedasticity-robust inference in linear regression models
published pages: , ISSN: , DOI: 10.17863/cam.41227
Cambridge Working Papers in Economics 1957 2020-01-23
2019 Jochmans, Koen; Weidner, Martin
Fixed-effect regressions on network data
published pages: , ISSN: 0012-9682, DOI: 10.17863/CAM.39733
Econometrica (2019) (In press). 1 2020-01-23
2019 Koen Jochmans Vincenzo Verardi
TWEXP and TWGRAVITY: Estimating exponential-regression models with two-way fixed effects
published pages: , ISSN: , DOI: 10.17863/cam.40109
Cambridge Working Papers in Economics 1945 2020-01-23
2019 Jochmans, Otsu
Likelihood Corrections for Two-way Models
published pages: 227, ISSN: 2115-4430, DOI: 10.15609/annaeconstat2009.134.0227
Annals of Economics and Statistics 134 2020-01-23
2019 Jochmans, Koen; Weidner, Martin
Inference on a distribution from noisy draws
published pages: , ISSN: , DOI: 10.17863/CAM.40110
Cambridge Working Papers in Economics 1946 2020-01-23
2019 Koen Jochmans
Testing for correlation in error-component models
published pages: , ISSN: , DOI: 10.17863/cam.37451
Cambridge Working Paper in Economics 1910 2020-01-23
2019 Koen Jochmans
A PORTMANTEAU TEST FOR CORRELATION IN SHORT PANELS
published pages: 1-8, ISSN: 0266-4666, DOI: 10.1017/s0266466619000203
Econometric Theory 2020-01-23
2017 Koen Jochmans, Thierry Magnac
A note on sufficiency in binary panel models
published pages: 259-269, ISSN: 1368-4221, DOI: 10.1111/ectj.12091
The Econometrics Journal 20/2 2020-01-23
2017 Koen Jochmans
Semiparametric Analysis of Network Formation
published pages: 705-713, ISSN: 0735-0015, DOI: 10.1080/07350015.2017.1286242
Journal of Business & Economic Statistics 36/4 2020-01-23
2017 Stéphane Bonhomme, Koen Jochmans, Jean-Marc Robin
Nonparametric estimation of non-exchangeable latent-variable models
published pages: 237-248, ISSN: 0304-4076, DOI: 10.1016/j.jeconom.2017.08.006
Journal of Econometrics 201/2 2020-01-23

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