{"title":"Accounting for Endogeneity in Regression Models Using Copulas: A Step-by-Step Guide for Empirical Studies","authors":"A. Papadopoulos","doi":"10.1515/jem-2020-0007","DOIUrl":"https://doi.org/10.1515/jem-2020-0007","url":null,"abstract":"Abstract We provide a detailed presentation and guide for the use of Copulas in order to account for endogeneity in linear regression models without the need for instrumental variables. We start by developing the model from first principles of likelihood inference, and then focus on the Gaussian Copula. We discuss its merits and propose diagnostics to assess its validity. We analyze in detail and provide solutions to the various issues that may arise in empirical applications for applying the method. We treat the cases of both continuous and discrete endogenous regressors. We present simulation evidence for the performance of the proposed model in finite samples, and we illustrate its application by a short empirical study. A Supplementary File contains additional simulations and another empirical illustration.","PeriodicalId":36727,"journal":{"name":"Journal of Econometric Methods","volume":"11 1","pages":"127 - 154"},"PeriodicalIF":0.0,"publicationDate":"2021-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1515/jem-2020-0007","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44500192","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
S. Caudill, Ksenija Bogosavljevic, Ken H. Johnson, F. Mixon
{"title":"Time on the Market and Probability of Sale Using a Generalized Geometric Hazard Model","authors":"S. Caudill, Ksenija Bogosavljevic, Ken H. Johnson, F. Mixon","doi":"10.1515/jem-2020-0017","DOIUrl":"https://doi.org/10.1515/jem-2020-0017","url":null,"abstract":"Abstract This study makes two main contributions to the applied econometrics literature. First, it shows how the all-important marginal effects for time on the market and probability of sale can be obtained from any hazard model. Second, it extends the generalization of the geometric due to Gómez-Déniz, E. 2010. “Another Generalization of the Geometric Distribution.” Test 19: 399–415 to include covariates for use in the estimation of time on the market and probability of sale regressions in real estate, thus creating an entirely new hazard model based on probability of sale rather than time on the market. For the generalized geometric we develop expressions for the marginal effects (with approximate standard errors) for both the probability of sale and time on the market. This formulation allows the impact of changes in independent variables on both the probability of sale and time on the market to be determined from a single regression model. For comparison, we also obtain these two sets of marginal effects for the popular Weibull hazard model. The geometric, generalized geometric, and Weibull hazard models, along with two sets of marginal effects for each, are estimated using data on condominium listings in a metropolitan area in Florida.","PeriodicalId":36727,"journal":{"name":"Journal of Econometric Methods","volume":"11 1","pages":"1 - 16"},"PeriodicalIF":0.0,"publicationDate":"2021-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1515/jem-2020-0017","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48401956","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"On the Implementation of Approximate Randomization Tests in Linear Models with a Small Number of Clusters","authors":"Y. Cai, Ivan A. Canay, Deborah Kim, A. Shaikh","doi":"10.1515/jem-2021-0030","DOIUrl":"https://doi.org/10.1515/jem-2021-0030","url":null,"abstract":"Abstract This paper provides a user’s guide to the general theory of approximate randomization tests developed in Canay, Romano, and Shaikh (2017a. “Randomization Tests under an Approximate Symmetry Assumption.” Econometrica 85 (3): 1013–30) when specialized to linear regressions with clustered data. An important feature of the methodology is that it applies to settings in which the number of clusters is small – even as small as five. We provide a step-by-step algorithmic description of how to implement the test and construct confidence intervals for the parameter of interest. In doing so, we additionally present three novel results concerning the methodology: we show that the method admits an equivalent implementation based on weighted scores; we show the test and confidence intervals are invariant to whether the test statistic is studentized or not; and we prove convexity of the confidence intervals for scalar parameters. We also articulate the main requirements underlying the test, emphasizing in particular common pitfalls that researchers may encounter. Finally, we illustrate the use of the methodology with two applications that further illuminate these points: one to a linear regression with clustered data based on Meng, Qian, and Yared (2015. “The Institutional Causes of china’s Great Famine, 1959–1961.” The Review of Economic Studies 82 (4): 1568–611) and a second to a linear regression with temporally dependent data based on Munyo and Rossi (2015. “First-day Criminal Recidivism.” Journal of Public Economics 124: 81–90). The companion R and Stata packages facilitate the implementation of the methodology and the replication of the empirical exercises.","PeriodicalId":36727,"journal":{"name":"Journal of Econometric Methods","volume":"12 1","pages":"85 - 103"},"PeriodicalIF":0.0,"publicationDate":"2021-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41905972","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Identification of Seasonal Effects in Impulse Responses Using Score-Driven Multivariate Location Models","authors":"Szabolcs Blazsek, A. Escribano, Adrián Licht","doi":"10.1515/jem-2020-0003","DOIUrl":"https://doi.org/10.1515/jem-2020-0003","url":null,"abstract":"Abstract For policy decisions, capturing seasonal effects in impulse responses are important for the correct specification of dynamic models that measure interaction effects for policy-relevant macroeconomic variables. In this paper, a new multivariate method is suggested, which uses the score-driven quasi-vector autoregressive (QVAR) model, to capture seasonal effects in impulse response functions (IRFs). The nonlinear QVAR-based method is compared with the existing linear VAR-based method. The following technical aspects of the new method are presented: (i) mathematical formulation of QVAR; (ii) first-order representation and infinite vector moving average, VMA (∞), representation of QVAR; (iii) IRF of QVAR; (iv) statistical inference of QVAR and conditions of consistency and asymptotic normality of the estimates. Control data are used for the period of 1987:Q1 to 2013:Q2, from the following policy-relevant macroeconomic variables: crude oil real price, United States (US) inflation rate, and US real gross domestic product (GDP). A graphical representation of seasonal effects among variables is provided, by using the IRF. According to the estimation results, annual seasonal effects are almost undetected by using the existing linear VAR tool, but those effects are detected by using the new QVAR tool.","PeriodicalId":36727,"journal":{"name":"Journal of Econometric Methods","volume":"10 1","pages":"53 - 66"},"PeriodicalIF":0.0,"publicationDate":"2020-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1515/jem-2020-0003","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48642646","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Danielle Handel, A. T. Ho, Kim P. Huynh, David T. Jacho-Chávez, Carson H. Rea
{"title":"Econometrics Pedagogy and Cloud Computing: Training the Next Generation of Economists and Data Scientists","authors":"Danielle Handel, A. T. Ho, Kim P. Huynh, David T. Jacho-Chávez, Carson H. Rea","doi":"10.1515/jem-2020-0012","DOIUrl":"https://doi.org/10.1515/jem-2020-0012","url":null,"abstract":"Abstract This paper describes how cloud computing tools widely used in the instruction of data scientists can be introduced and taught to economics students as part of their curriculum. The demonstration centers around a workflow where the instructor creates a virtual server and the students only need Internet access and a web browser to complete in-class tutorials, assignments, or exams. Given how prevalent cloud computing platforms are becoming for data science, introducing these techniques into students’ econometrics training would prepare them to be more competitive when job hunting, while making instructors and administrators re-think what a computer laboratory means on campus.","PeriodicalId":36727,"journal":{"name":"Journal of Econometric Methods","volume":"10 1","pages":"89 - 102"},"PeriodicalIF":0.0,"publicationDate":"2020-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1515/jem-2020-0012","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43110013","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Identifying Causal Channels of Policy Reforms with Multiple Treatments and Different Types of Selection","authors":"Annabelle Doerr, Anthony Strittmatter","doi":"10.1515/jem-2019-0012","DOIUrl":"https://doi.org/10.1515/jem-2019-0012","url":null,"abstract":"Abstract We study the identification of channels of policy reforms with multiple treatments and different types of selection for each treatment. We disentangle reform effects into policy effects, selection effects, and time effects under the assumption of conditional independence, common trends, and an additional exclusion restriction on the non-treated. Furthermore, we show the identification of direct- and indirect policy effects after imposing additional sequential conditional independence assumptions on mediating variables. We illustrate the approach using the German reform of the allocation system of vocational training for unemployed persons. The reform changed the allocation of training from a mandatory system to a voluntary voucher system. Simultaneously, the selection criteria for participants changed, and the reform altered the composition of course types. We consider the course composition as a mediator of the policy reform. We show that the empirical evidence from previous studies reverses when considering the course composition. This has important implications for policy conclusions.","PeriodicalId":36727,"journal":{"name":"Journal of Econometric Methods","volume":"10 1","pages":"67 - 88"},"PeriodicalIF":0.0,"publicationDate":"2020-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1515/jem-2019-0012","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42670116","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Time–Frequency Regression","authors":"Yoshito Funashima","doi":"10.1515/jem-2019-0025","DOIUrl":"https://doi.org/10.1515/jem-2019-0025","url":null,"abstract":"Abstract Wavelet analysis is widely used to trace macroeconomic and financial phenomena in time–frequency domains. However, existing wavelet measures diverge from conventional regression estimators. Furthermore, a direct comparison between wavelet and traditional regression analyses is difficult. In this study, we modify the partial wavelet gain to provide an estimator that corresponds to the ordinary least squares estimator at each point of the time–frequency space. We argue that from the viewpoint of practical applications, the modified partial wavelet gain is suitable for contemporary regressions across time and frequencies, whereas the original partial wavelet gain is suitable for evaluating an aggregate relationship of contemporaneous and lead-lag relationships.","PeriodicalId":36727,"journal":{"name":"Journal of Econometric Methods","volume":"10 1","pages":"21 - 32"},"PeriodicalIF":0.0,"publicationDate":"2020-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1515/jem-2019-0025","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44928946","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Simple Multivariate Conditional Covariance Dynamics Using Hyperbolically Weighted Moving Averages","authors":"H. Kawakatsu","doi":"10.1515/jem-2020-0004","DOIUrl":"https://doi.org/10.1515/jem-2020-0004","url":null,"abstract":"Abstract This paper considers a class of multivariate ARCH models with scalar weights. A new specification with hyperbolic weighted moving average (HWMA) is proposed as an analogue of the EWMA model. Despite the restrictive dynamics of a scalar weight model, the proposed model has a number of advantages that can deal with the curse of dimensionality. The empirical application illustrates that the (pseudo) out-of-sample multistep forecasts can be surprisingly more accurate than those from the DCC model.","PeriodicalId":36727,"journal":{"name":"Journal of Econometric Methods","volume":"10 1","pages":"33 - 52"},"PeriodicalIF":0.0,"publicationDate":"2020-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1515/jem-2020-0004","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44018717","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Maximum Entropy Analysis of Consumption-based Capital Asset Pricing Model and Volatility","authors":"Tae-Hwy Lee, Millie Yi Mao, A. Ullah","doi":"10.1515/jem-2019-0022","DOIUrl":"https://doi.org/10.1515/jem-2019-0022","url":null,"abstract":"Abstract Based on the maximum entropy (ME) method, we introduce an information theoretic approach to estimating conditional moment functions with incorporating a theoretical constraint implied from the consumption-based capital asset pricing model (CCAPM). Using the ME conditional mean/variance functions obtained from the ME density, we analyze the relationship between asset returns and consumption growth under the theoretical constraint of the CCAPM. We evaluate the predictability of asset return using consumption growth through in-sample estimation and out-of-sample prediction in the ME mean regression function. We also examine the ME variance regression function for the asset return volatility as a function of the consumption growth. Our findings suggest that incorporating the CCAPM constraint can capture the nonlinear predictability of asset returns in mean especially in tails, and that the consumption growth has an effect on reducing stock return volatility, indicating the counter-cyclical variation of stock market volatility.","PeriodicalId":36727,"journal":{"name":"Journal of Econometric Methods","volume":"10 1","pages":"1 - 19"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1515/jem-2019-0022","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41935487","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}