HEN: Econometrics (Topic)最新文献

{"title":"Testing for Idiosyncratic Treatment Effect Heterogeneity","authors":"Jaime Ramirez-Cuellar","doi":"10.2139/ssrn.3946092","DOIUrl":"https://doi.org/10.2139/ssrn.3946092","url":null,"abstract":"This paper provides asymptotically valid tests for the null hypothesis of no treatment effect heterogeneity. Importantly, I consider the presence of heterogeneity that is not explained by observed characteristics, or so-called idiosyncratic heterogeneity. When examining this heterogeneity, common statistical tests encounter a nuisance parameter problem in the average treatment effect which renders the asymptotic distribution of the test statistic dependent on that parameter. I propose an asymptotically valid test that circumvents the estimation of that parameter using the empirical characteristic function. A simulation study illustrates not only the test's validity but its higher power in rejecting a false null as compared to current tests. Furthermore, I show the method's usefulness through its application to a microfinance experiment in Bosnia and Herzegovina. In this experiment and for outcomes related to loan take-up and self-employment, the tests suggest that treatment effect heterogeneity does not seem to be completely accounted for by baseline characteristics. For those outcomes, researchers could potentially try to collect more baseline characteristics to inspect the remaining treatment effect heterogeneity, and potentially, improve treatment targeting.","PeriodicalId":436489,"journal":{"name":"HEN: Econometrics (Topic)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126878677","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":"Regional Interdependence of the Japan REIT Market: A Heteroscedasticity-Robust Time Series Approach","authors":"Kaiji Motegi, Yoshitaka Iitsuka","doi":"10.2139/ssrn.3902176","DOIUrl":"https://doi.org/10.2139/ssrn.3902176","url":null,"abstract":"This paper investigates the dynamic interdependence between the stock returns of regionally disjoint Japanese real estate investment trusts (REITs), where the property type and a market return are controlled. We take a multivariate time series approach with the error term being allowed to have conditional heteroscedasticity of unknown form. We find significant spillover effects from central to local areas in conditional mean, a potential signal of arbitrage opportunities. The spillover effects have become stronger after the COVID-19 crisis for the office and hotel sectors, but not for the residential sector. This contrast suggests that a geographic diversification strategy within residential REIT securities should be more effective than that within office or hotel, especially during a period of turmoil.","PeriodicalId":436489,"journal":{"name":"HEN: Econometrics (Topic)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123743587","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":"The Effect of Health Care Policy Uncertainty on Households' Consumption and Portfolio Choice","authors":"T. Wiemann, R. Lumsdaine","doi":"10.2139/ssrn.3418411","DOIUrl":"https://doi.org/10.2139/ssrn.3418411","url":null,"abstract":"With medical expenditures constituting an increasingly large share of private spending, the continuing policy debate on health care reform in the United States is a potentially important source of households’ financial uncertainty. To quantify the implications of this uncertainty for the real economy, this paper conducts an empirical analysis of the effect of health care policy uncertainty (HCPU) on two channels of households’ economic behavior: consumption and portfolio choice. Using a simple model to illustrate a heterogeneous effect of HCPU, we develop an identification strategy that exploits variation in health to capture exposure to these policy uncertainty shocks. Two complementary semiparametric heterogeneous effects models are introduced that are particularly suited to the analysis of empirically unobserved variables such as health. The results indicate an important effect of HCPU on portfolio choice but provide mixed evidence for the effect on households' total spending. Our estimates corroborate the theoretical prediction that this effect is increasing in households' health problems.","PeriodicalId":436489,"journal":{"name":"HEN: Econometrics (Topic)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126866408","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":"Three Essays on Nonlinear Time-series Econometrics","authors":"Charles Shaw","doi":"10.2139/ssrn.3323449","DOIUrl":"https://doi.org/10.2139/ssrn.3323449","url":null,"abstract":"This thesis is submitted in three chapters.<br><br>Chapter 1 considers a regime-switching Levy framework, where all parameter values depend on the value of a continuous time Markov chain as per Chevallier and Goutte (2017), is employed to study US Corporate Option-Adjusted Spreads (OASs). For modelling purposes we assume a Normal Inverse Gaussian distribution, allowing heavier tails and skewness. After the Expectation - Maximization algorithm is applied to this general class of regime switching models, we compare the obtained results with time series models without jumps, including one with regime switching and one without. We find that a regime-switching Levy model clearly defines two regimes for A-, AA-, and AAA-rated OASs. We find further evidence of regime-switching effects, with data showing relatively pronounced jump intensity around the time of major crisis periods, thereby confirming the presence and importance of volatility regimes. Results indicate that ignoring the complex and dynamic dependence structure in favour of certain model assumptions may lead to a significant underestimation of risk. To the best of our knowledge, this study is the first time that Markov-switching Levy models have been employed to analyze the structure of option-adjusted spreads.<br><br>Chapter 2 considers a little-used dataset to study the Japan's Real Estate Investment Trusts (REITs) market. We make use of copula theory and test for dependence between equity and REIT returns using several popular copula families. The copula families in our specification were: Gaussian, Student-$t$, Clayton, Frank, and Gumbel. The p-values were computed using parametric bootstrap replications. We motivate the argument presented, and provide the goodness-of-fit test results based on the Rosenblatt transform. We find that the dependence between the innovations of JREIT Composite and JREIT Office returns can be modelled by a Student-$t$ copula with 2.7 degrees of freedom and correlation parameter $hat{nu}$ = 0.93. All other models are rejected. To the best of our knowledge, this study represents the first time that copula theory has been applied to study REITs in Japan.<br><br>Chapter 3 critiques a recent contribution to the financial econometrics literature, namely Chu et al. (2017), which provides the first examination of the time-series price behaviour of the most popular cryptocurrencies. We argue that insufficient attention was paid to correctly diagnosing the distribution of GARCH innovations. When these data issues are controlled for, their results lack robustness and may lead to either underestimation or overestimation of future risks. The main aim of this paper therefore is to provide an improved econometric specification. Particular attention is paid to correctly diagnosing the distribution of GARCH innovations by means of Kolmogorov type non-parametric tests and Khmaladze's martingale transformation. Numerical computation is carried out by implementing a Gauss-Kronrod","PeriodicalId":436489,"journal":{"name":"HEN: Econometrics (Topic)","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128810857","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":"Modelling Housing Need in Australia to 2025","authors":"Steven Rowley, C. Leishman, E. Baker, R. Bentley, L. Lester","doi":"10.18408/AHURI-8106901","DOIUrl":"https://doi.org/10.18408/AHURI-8106901","url":null,"abstract":"This research developed a housing need simulation to quantify the need for affordable housing and identify the supply required to meet the demand for housing. This information is important for resource allocation, market monitoring, setting affordable housing targets, housing assistance budgeting and evidence for affordable housing contributions via planning policy.","PeriodicalId":436489,"journal":{"name":"HEN: Econometrics (Topic)","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114726734","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":"Koşullu Volatilitenin Modellenmesinde Destek Vektör Makinesi GARCH Modeli Ve Türk Finans Piyasaları Üzerine Bir Uygulama (Support Vector Machine GARCH Model in Modelling Conditional Volatility and an Application to Turkish Financial Markets)","authors":"M. Bildirici, Ozgur Omer Ersin","doi":"10.2139/ssrn.2222071","DOIUrl":"https://doi.org/10.2139/ssrn.2222071","url":null,"abstract":"The English version of this paper can be found at: http://ssrn.com/abstract=2227747Calisma, temel GARCH modelinin Destek Vektor Makinesi ve Yapay Sinir Aglari ile iyilestirilmis modellerin incelenerek GARCH modelinin tahmin performansinin iyilestirilmesi bakimindan basarisinin test edilmesini amaclamaktadir. YSA yapisinin temel alindigi NN-GARCH modelinde Donaldson ve Kamstra (1997) NN-GARCH mimarisinin temel alindigi ve farkli ogrenme algoritmalari ile modellendigi Bildirici ve Ersin (2009) temel alinirken, SVR-GARCH modelinin olusturulmasinda Ou ve Wang (2010) ve Perez-Cruz (2003) calismalarindan hareket edilmistir. Modeller, tahmin basarisi bakimindan degerlendirilmistir. Bu kapsamda, IMKB-100 endeksinde gunluk getiriler modellenmesinde temel alinan GARCH, SVR-GARCH ve MLP-GARCH modelleri, orneklem ici ve orneklem disi tahmin basarisi acisindan degerlendirilmistir. Ampirik bulgular cercevesinde, seride one cikan leptokurtik dagilima ek olarak asimetri ve dogrusal olmama karakteristiklerinin SVR-GARCH ve MLP-GARCH modelleri ile modellenebilecegi; farkli hata kriterleri ve esit tahmin tutarliligi testleri kapsaminda temel GARCH modellerinden basarili bulundugu; orneklem disi tahmin basarisi bakimindan ise, Diebold Mariano testlerinden hareketle SVR-GARCH ve MLP-GARCH modelleri icin esit tahmin tutarliliginin 8 farkli gelecek tahmininden 6'si icin reddedilememekte iken; 2'si icin ise SVR-GARCH modelinin daha basarili bulundugu sonuclarina varilmaktadir. The study aims to augment commonly applied volatility models with support vector machines and neural networks. The proposed modeling strategy benefits from neural network based GARCH models of Donaldson and Kamstra (1997) and SVR-GARCH models discussed by Ou and Wang (2010) and Perez-Cruz (2003). Models are evaluated for in-sample and out-of-sample forecasting of daily returns in Istanbul ISE100 stock index. Results suggest that volatility clustering, asymmetry and nonlinearity characteristics are modeled more effectively with SVR-GARCH and MLP-GARCH models compared to the basic GARCH models. In terms of out-of-sample forecasting capabilities, Diebold-Mariano tests show that equal forecast accuracy could not be rejected for most of the horizons for the MLP-GARCH and SVR-GARCH models. On the other hand, SVR-GARCH is found to possess better forecast accuracy in 2 out of 8 forecast competitions.","PeriodicalId":436489,"journal":{"name":"HEN: Econometrics (Topic)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131020159","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":"Measuring the Effects of Removing Subsidies for Private Insurance on Public Expenditure for Health Care","authors":"T. Cheng","doi":"10.2139/ssrn.1961524","DOIUrl":"https://doi.org/10.2139/ssrn.1961524","url":null,"abstract":"This paper investigates the effects of removing subsidies for private health insurance on public sector expenditure for hospital care. An econometric framework using simultaneous equation models is developed to analyze the interrelated decisions on the intensity and type of health care use and insurance. The results indicate that while privately insured individuals are more likely to seek hospital care as a private patient, they do not differ in the intensity of hospital care use compared with those without private insurance. The simulation results suggest that eliminating subsides could potentially yield substantial public sector savings.","PeriodicalId":436489,"journal":{"name":"HEN: Econometrics (Topic)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128062204","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":"Marginal Effects in Multivariate Probit and Kindred Discrete and Count Outcome Models, with Applications in Health Economics","authors":"J. Mullahy","doi":"10.3386/W17588","DOIUrl":"https://doi.org/10.3386/W17588","url":null,"abstract":"Estimation of marginal or partial effects of covariates x on various conditional parameters or functionals is often the main target of applied microeconometric analysis. In the specific context of probit models, estimation of partial effects involving outcome probabilities will often be of interest. Such estimation is straightforward in univariate models, and Greene, 1996, 1998, has extended these results to cover the case of quadrant probability marginal effects in bivariate probit models. The first purpose of this paper is to extend these results to encompass the general !\"!# multivariate probit (MVP) context for arbitrary orthant probabilities. It is suggested that such partial effects are broadly useful in situations wherein multivariate outcomes are of concern. The paper derives the general result on orthant probability partial effects, which contains Greene's bivariate result as a special case. These results are then extended to models that condition on subvectors of y, to count data structures that derive from the probability structure of y, to multivariate ordered probit data structures, and to the multinomial probit model whose marginal effects turn out to be a special case of those of the multivariate probit model. Numerical simulations suggest that use of the analytical formulae versus fully numerical","PeriodicalId":436489,"journal":{"name":"HEN: Econometrics (Topic)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132035807","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":"Attrition and Health in Ageing Studies: Evidence from ELSA and HRS","authors":"J. Banks, Alastair Muriel, James P. Smith","doi":"10.2139/ssrn.1680647","DOIUrl":"https://doi.org/10.2139/ssrn.1680647","url":null,"abstract":"In this paper we present results of an investigation into observable characteristics associated with attrition in ELSA and the HRS, with a particular focus on whether attrition is systematically related to health outcomes and socioeconomic status (SES). Investigating the links between health and SES is one of the primary goals of the ELSA and HRS, so attrition correlated with these outcomes is a critical concern. We explored some possible reasons for these differences. Survey maturity, mobility, respondent burden, interviewer quality, and differing sampling methods all fail to account for the gap. Differential respondent incentives may play some role, but the impact of respondent incentive is difficult to test. Apparently, cultural differences between the US and Europe population in agreeing to participate and remain in scientific surveys are a more likely explanation.","PeriodicalId":436489,"journal":{"name":"HEN: Econometrics (Topic)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115825422","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":"Use of Propensity Scores in Non-Linear Response Models: The Case for Health Care Expenditures","authors":"A. Basu, D. Polsky, W. Manning","doi":"10.3386/W14086","DOIUrl":"https://doi.org/10.3386/W14086","url":null,"abstract":"Under the assumption of no unmeasured confounders, a large literature exists on methods that can be used to estimating average treatment effects (ATE) from observational data and that spans regression models, propensity score adjustments using stratification, weighting or regression and even the combination of both as in doubly-robust estimators. However, comparison of these alternative methods is sparse in the context of data generated via non-linear models where treatment effects are heterogeneous, such as is in the case of healthcare cost data. In this paper, we compare the performance of alternative regression and propensity score-based estimators in estimating average treatment effects on outcomes that are generated via non-linear models. Using simulations, we find that in moderate size samples (n= 5000), balancing on estimated propensity scores balances the covariate means across treatment arms but fails to balance higher-order moments and covariances amongst covariates, raising concern about its use in non-linear outcomes generating mechanisms. We also find that besides inverse-probability weighting (IPW) with propensity scores, no one estimator is consistent under all data generating mechanisms. The IPW estimator is itself prone to inconsistency due to misspecification of the model for estimating propensity scores. Even when it is consistent, the IPW estimator is usually extremely inefficient. Thus care should be taken before naively applying any one estimator to estimate ATE in these data. We develop a recommendation for an algorithm which may help applied researchers to arrive at the optimal estimator. We illustrate the application of this algorithm and also the performance of alternative methods in a cost dataset on breast cancer treatment.","PeriodicalId":436489,"journal":{"name":"HEN: Econometrics (Topic)","volume":"29 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130375381","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}