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Articles 1 - 20 of 20
Full-Text Articles in Econometrics
Nonstationary Heterogeneous Panels With Multiple Structural Changes, Badi H. Baltagi, Qu Feng, Wei Wang
Nonstationary Heterogeneous Panels With Multiple Structural Changes, Badi H. Baltagi, Qu Feng, Wei Wang
Center for Policy Research
Nonstationary panels have been widely used in empirical studies in macroeconomics and finance. This paper considers multiple structural changes in nonstationary heterogeneous panels with common factors. Kapetanios, Pesaran, Yamagata (2011) showed that unobserved nonstationary factors can be proxied by cross-sectional averages of observable data. This means that unobserved error factors can be treated as additional regressors, and different break points in slopes and error factor loadings can be considered as multiple breaks in linear regression models with panel data. We generalize the least squares approach by Bai and Perron (1998) to nonstationary panels and show that the break points in …
Low-Rank Panel Quantile Regression: Estimation And Inference, Yiren Wang, Yichong Zhang, Yichong Zhang
Low-Rank Panel Quantile Regression: Estimation And Inference, Yiren Wang, Yichong Zhang, Yichong Zhang
Research Collection School Of Economics
In this paper, we propose a class of low-rank panel quantile regression models which allow for unobserved slope heterogeneity over both individuals and time. We estimate the heterogeneous intercept and slope matrices via nuclear norm regularization followed by sample splitting, row- and column-wise quantile regressions and debiasing. We show that the estimators of the factors and factor loadings associated with the intercept and slope matrices are asymptotically normally distributed. In addition, we develop two specification tests: one for the null hypothesis that the slope coefficient is a constant over time and/or individuals under the case that true rank of slope …
Identifying Latent Grouped Patterns In Conintegrated Panels, Wenxin Huang, Sainan Jin, Liangjun Su
Identifying Latent Grouped Patterns In Conintegrated Panels, Wenxin Huang, Sainan Jin, Liangjun Su
Research Collection School Of Economics
We consider a panel cointegration model with latent group structures that allows for heterogeneous long-run relationships across groups. We extend Su, Shi, and Phillips (2016, Econometrica 84(6), 2215-2264) classifier-Lasso (C-Lasso) method to the nonstationary panels and allow for the presence of endogeneity in both the stationary and nonstationary regressors in the model. In addition, we allow the dimension of the stationary regressors to diverge with the sample size. We show that we can identify the individuals' group membership and estimate the group-specific long-run cointegrated relationships simultaneously. We demonstrate the desirable property of uniform classification consistency and the oracle properties of …
Identifying Latent Grouped Patterns In Cointegrated Panels, Wenxin Huang, Sainan Jin, Liangjun Su
Identifying Latent Grouped Patterns In Cointegrated Panels, Wenxin Huang, Sainan Jin, Liangjun Su
Research Collection School Of Economics
We consider a panel cointegration model with latent group structures that allows for heterogeneous long-run relationships across groups. We extend Su, Shi, and Phillips (2016, Econometrica 84(6), 2215-2264) classifier-Lasso (C-Lasso) method to the nonstationary panels and allow for the presence of endogeneity in both the stationary and nonstationary regressors in the model. In addition, we allow the dimension of the stationary regressors to diverge with the sample size. We show that we can identify the individuals' group membership and estimate the group-specific long-run cointegrated relationships simultaneously. We demonstrate the desirable property of uniform classification consistency and the oracle properties of …
Sieve Estimation Of Time-Varying Panel Data Models With Latent Structures, Liangjun Su, Xia Wang, Sainan Jin
Sieve Estimation Of Time-Varying Panel Data Models With Latent Structures, Liangjun Su, Xia Wang, Sainan Jin
Research Collection School Of Economics
We propose a heterogeneous time-varying panel data model with a latent group structure that allows the coefficients to vary over both individuals and time. We assume that the coefficients change smoothly over time and form different unobserved groups. When treated as smooth functions of time, the individual functional coefficients are heterogeneous across groups but homogeneous within a group. We propose a penalized-sieve-estimation-based classifier-Lasso (C-Lasso) procedure to identify the individuals’ membership and to estimate the group-specific functional coefficients in a single step. The classification exhibits the desirable property of uniform consistency. The C-Lasso estimators and their post-Lasso versions achieve the oracle …
The Effect Of Social Information In The Dictator Game With A Taking Option, Tanya O'Garra, Valerio Capraro, Praveen Kujal
The Effect Of Social Information In The Dictator Game With A Taking Option, Tanya O'Garra, Valerio Capraro, Praveen Kujal
ESI Working Papers
We experimentally study how redistribution choices are affected by positive and negative information regarding the behaviour of a previous participant in a dictator game with a taking option. We use the strategy method to identify behavioural ‘types’, and thus distinguish ‘conformists’ from ‘counter-conformists’, and unconditional choosers. Unconditional choosers make up the greatest proportion of types (about 80%) while only about 20% of subjects condition their responses to social information. We find that both conformity and counter-conformity are driven by a desire to be seen as moral (the ‘symbolization’ dimension of moral identity). The main difference is that, conformity is also …
Sieve Estimation Of Time-Varying Panel Data Models With Latent Structures, Liangjun Su, Xia Wang, Sainan Jin
Sieve Estimation Of Time-Varying Panel Data Models With Latent Structures, Liangjun Su, Xia Wang, Sainan Jin
Research Collection School Of Economics
We propose a heterogeneous time-varying panel data model with a latent group structure that allows the coefficients to vary over both individuals and time. We assume that the coefficients change smoothly over time and form different unobserved groups. When treated as smooth functions of time, the individual functional coefficients are heterogeneous across groups but homogeneous within a group. We propose a penalized-sieve-estimation-based classifier-Lasso (C-Lasso) procedure to identify the individuals’ membership and to estimate the group-specific functional coefficients in a single step. The classification exhibits the desirable property of uniform consistency. The C-Lasso estimators and their post-Lasso versions achieve the oracle …
Identifying Latent Grouped Patterns In Cointegrated Panels, Wenxin Huang, Sainan Jin, Liangjun Su
Identifying Latent Grouped Patterns In Cointegrated Panels, Wenxin Huang, Sainan Jin, Liangjun Su
Research Collection School Of Economics
We consider a panel cointegration model with latent group structures that allows for heterogeneous long-run relationships across groups. We extend Su, Shi, and Phillips’ (2016) classifier-Lasso (C-Lasso) method to the nonstationary panels and allow for the presence of endogeneity in both the stationary and nonstationary regressors in the model. In addition, we allow the dimension of the stationary regressors to diverge with the sample size. We show that we can identify the individuals’ group membership and estimate the group-specific long-run cointegrated relationships simultaneously. We demonstrate the desirable property of uniform classification consistency and the oracle properties of both the C-Lasso …
Accounting For Locational, Temporal, And Physical Similarity Of Residential Sales In Mass Appraisal Modeling: The Development And Application Of Geographically, Temporally, And Characteristically Weighted Regression, Paul E. Bidanset, Michael Mccord, John R. Lombard, Peadar Davis, William J. Mccluskey
Accounting For Locational, Temporal, And Physical Similarity Of Residential Sales In Mass Appraisal Modeling: The Development And Application Of Geographically, Temporally, And Characteristically Weighted Regression, Paul E. Bidanset, Michael Mccord, John R. Lombard, Peadar Davis, William J. Mccluskey
School of Public Service Faculty Publications
Geographically weighted regression (GWR) has been recognized in the assessment community as a viable automated valuation model (AVM) to help overcome, at least in part, modeling hurdles associated with location, such as spatial heterogeneity and spatial autocorrelation of error terms. Although previous researchers have adjusted the GWR weights matrix to also weight by time of sale or by structural similarity of properties in AVMs, the research described in this paper is the first that has done so by all three dimensions (i.e., location, structural similarity, and time of sale) simultaneously. Using 24 years of single-family residential sales in Fairfax, Virginia, …
Empirical Study Of Online Horse Race Bettors Betting Behavior In Finland, Tuomo Kainulainen
Empirical Study Of Online Horse Race Bettors Betting Behavior In Finland, Tuomo Kainulainen
International Conference on Gambling & Risk Taking
This presentation produces an overview of online horse race bettors’ betting behavior in the Finnish betting market. The following studies have utilized individual-level online betting data LaPlante et al. (2006), LaBrie et al. (2007), LaBrie et al. (2008), LaPlante et al. (2009), Xuan & Shaffer (2009), Braveman & Shaffer (2010), Dragicevic et al. (2011), Fiedler (2013) and Gainsbury & Russell (2013). These studies focus on sports betting, poker and casino games. As an addition to the betting behavioural literature, this study focuses on horse race betting by utilizing betting data provided by Fintoto Ltd which has a legal monopoly for …
Sieve Instrumental Variable Quantile Regression Estimation Of Functional Coefficient Models, Liangjun Su, Tadao Hoshino
Sieve Instrumental Variable Quantile Regression Estimation Of Functional Coefficient Models, Liangjun Su, Tadao Hoshino
Research Collection School Of Economics
In this paper we consider sieve instrumental variable quantile regression (IVQR) estimation of functional coefficient models where the coefficients of endogenous regressors are unknown functions of some exogenous covariates. We estimate the functional coefficients by the sieve-IVQR technique and establish the uniform consistency and asymptotic normality of the estimators. Based on the sieve estimates, we propose a nonparametric specification test for the constancy of the functional coefficients and study its asymptotic. We conduct simulations to evaluate the finite sample behavior of our estimator and test statistic, and apply our method to study the estimation of quantile Engel curves.
Sieve Estimation Of Time-Varying Panel Data Models With Latent Structures, Liangjun Su, Xia Wang, Sainan Jin
Sieve Estimation Of Time-Varying Panel Data Models With Latent Structures, Liangjun Su, Xia Wang, Sainan Jin
Research Collection School Of Economics
We consider the problem of determining the number of factors and selecting the proper regressors in linear dynamic panel data models with interactive fixed effects. Based on the preliminary estimates of the slope parameters and factors a la Bai and Ng (2009) and Moon andWeidner (2014a), we propose a method for simultaneous selection of regressors and factors and estimation through the method of adaptive group Lasso (least absolute shrinkage and selection operator). We show that with probability approaching one, our method can correctly select all relevant regressors and factors and shrink the coefficients of irrelevant regressors and redundant factors to …
Sieve Instrumental Variable Quantile Regression Estimation Of Functional Coefficient Models, Liangjun Su, Tadao Hoshina
Sieve Instrumental Variable Quantile Regression Estimation Of Functional Coefficient Models, Liangjun Su, Tadao Hoshina
Research Collection School Of Economics
In this paper, we consider sieve instrumental variable quantile regression (IVQR) estimation of functional coefficient models where the coefficients of endogenous regressors are unknown functions of some exogenous covariates. We approximate the unknown functional coefficients by some basis functions and estimate them by the IVQR technique. We establish the uniform consistency and asymptotic normality of the estimators of the functional coefficients. Based on the sieve estimates, we propose a nonparametric specification test for the constancy of the functional coefficients, study its asymptotic properties under the null hypothesis, a sequence of local alternatives and global alternatives, and propose a wild-bootstrap procedure …
Testing Homogeneity In Panel Data Models With Interactive Fixed Effects, Liangjun Su, Qihui Chen
Testing Homogeneity In Panel Data Models With Interactive Fixed Effects, Liangjun Su, Qihui Chen
Research Collection School Of Economics
This paper proposes a residual-based LM test for slope homogeneity in large dimensional panel data models with interactive fixed effects. We first run the panel regression under the null to obtain the restricted residuals, and then use them to construct our LM test statistic. We show that after being appropriately centered and scaled, our test statistic is asymptotically normally distributed under the null and a sequence of Pitman local alternatives. The asymptotic distributional theories are established under fairly general conditions which allow for both lagged dependent variables and conditional heteroskedasticity of unknown form by relying on the concept of conditional …
Local Linear Gmm Estimation Of Functional Coefficient Iv Models With Application To The Estimation Of Rate Of Return To Schooling, Liangjun Su, Irina Murtazashvili, Aman Ullah
Local Linear Gmm Estimation Of Functional Coefficient Iv Models With Application To The Estimation Of Rate Of Return To Schooling, Liangjun Su, Irina Murtazashvili, Aman Ullah
Research Collection School Of Economics
We consider the local linear GMM estimation of functional coe cient models with a mix of discrete and continuous data and in the presence of endogenous regressors. We establish the asymptotic normality of the estimator and derive the optimal instrumental variable that minimizes the asymptotic variance-covariance matrix among the class of all local linear GMM estimators. Data-dependent bandwidth sequences are also allowed for. We propose a nonparametric test for the constancy of the functional coefficients, study its asymptotic properties under the null hypothesis as well as a sequence of local alternatives and global alternatives, and propose a bootstrap version for …
Pricing For Goodwill: A Threshold Quantile Regression Approach, Heng Ju, Liangjun Su, Pai Xu
Pricing For Goodwill: A Threshold Quantile Regression Approach, Heng Ju, Liangjun Su, Pai Xu
Research Collection School Of Economics
In the absence of other effective trust systems, an agent's reputation status becomes a critical factor in online transactions. A higher reputation category may give sellers an advantage in competition on online trading platforms. It is also possible that such reputation benefits provide sufficient incentives for sellers to adjust their pricing behavior. We here propose a simple economic model in which an online seller maximizes the sum of the profit from current sales and the possible future gain from a targeted higher reputation level. We show that the model can predict a jump in optimal pricing behavior. We adopt a …
Buyer's Equilibrium With Capacity Constraints And Restricted Mobility: A Recursive Approach, Gabriele Camera, Jaehong Kim
Buyer's Equilibrium With Capacity Constraints And Restricted Mobility: A Recursive Approach, Gabriele Camera, Jaehong Kim
ESI Working Papers
We study a decentralized trading model as in Peters (1984), where heterogeneous market participants face a trade-o between price and trade probability. We present a novel proof of existence of a unique demand vector in Nash equilibrium, based on a recursive approach that exploits the monotonicity of matching functions.
Testing Heterogeneity In Panel Data Models With Interactive Fixed Effects, Qihui Chen
Testing Heterogeneity In Panel Data Models With Interactive Fixed Effects, Qihui Chen
Dissertations and Theses Collection (Open Access)
This paper proposes a test for the slope homogeneity in large dimensional panel data models with interactive fixed effects based on a measure of goodness-of-fit (R2). We first obtain, for each cross-sectional unit, the R2 from the time series regression of residuals on the constant and observable regressors and then construct the test statistic R2 as an equally weighted average of the cross-sectional R2's. R̄2 is close to 0 under the null hypothesis of homogenous slopes and deviates away from 0 otherwise. We show that after being appropriately centered and scaled, R2 …
Adaptive Estimation Of Autoregressive Models With Time-Varying Variances, Ke-Li Xu, Peter C. B. Phillips
Adaptive Estimation Of Autoregressive Models With Time-Varying Variances, Ke-Li Xu, Peter C. B. Phillips
Research Collection School Of Economics
Stable autoregressive models are considered with martingale differences errors scaled by an unknown nonparametric time-varying function generating heterogeneity. An important special case involves structural change in the error variance, but in most practical cases the pattern of variance change over time is unknown and may involve shifts at unknown discrete points in time, continuous evolution or combinations of the two. This paper develops kernel-based estimators of the residual variances and associated adaptive least squares (ALS) estimators of the autoregressive coefficients. Simulations show that efficiency gains are achieved by the adaptive procedure.
Some Empirics On Economic Growth Under Heterogeneous Technology, Peter C. B. Phillips, Donggyu Sul
Some Empirics On Economic Growth Under Heterogeneous Technology, Peter C. B. Phillips, Donggyu Sul
Research Collection School Of Economics
A new econometric approach to testing for economic growth convergence is overviewed. The method is applicable to panel data, involves a simple regression based one-sided t-test, and can be used to form a clustering algorithm to assess the existence of growth convergence clubs. The approach allows for heterogeneous technology, utilizes some new asymptotic theory for nonlinear dynamic factor models, and is easy to implement. Some background growth theory is given which shows the form of augmented Solow regression (ASR) equations in the presence of heterogeneous technology and explains sources of potential misspecification that can arise in conventional formulations of ASR …