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Sorawoot Srisuma

Publications and source records attributed to Sorawoot Srisuma.

4 recordsLinked to original sources

Identification and Estimation of Seller Risk Aversion in Ascending Auctions

This paper shows how to identify and estimate the seller's risk parameter in an ascending auction. We consider a semiparametric model where the seller has a parametric utility function (such as CARA or CRRA) and the distribution of bidder valuations is modeled flexibly. We provide primitive conditions under which the risk parameter is identified and show that it can be consistently estimated with an asymptotically normal limiting distribution under standard regularity conditions. A Monte Carlo study demonstrates good finite-sample performance of the proposed estimator. We apply our approach to foreclosure real estate auction data from São Paulo. We find evidence that sellers are risk-averse, which leads to a much better fit to the data than a model with risk-neutral sellers, which would substantially underpredict the reserve price relative to what is observed.

econ.EM

Wald inference on varying coefficients

We present simple to implement Wald-type statistics that deliver a general nonparametric inference theory for linear restrictions on varying coefficients in a range of regression models allowing for cross-sectional or spatial dependence. We provide a general central limit theorem that covers a broad range of error spatial dependence structures, allows for a degree of misspecification robustness via nonparametric spatial weights and permits inference on both varying regression and spatial dependence parameters. Using our method, we first uncover evidence of constant returns to scale in the Chinese nonmetal mineral industry's production function, and then show that Boston house prices respond nonlinearly to proximity to employment centers. A simulation study confirms that our tests perform very well in finite samples.

econ.EM

Robust Ranking of Happiness Outcomes: A Median Regression Perspective

Ordered probit and logit models have been frequently used to estimate the mean ranking of happiness outcomes (and other ordinal data) across groups. However, it has been recently highlighted that such ranking may not be identified in most happiness applications. We suggest researchers focus on median comparison instead of the mean. This is because the median rank can be identified even if the mean rank is not. Furthermore, median ranks in probit and logit models can be readily estimated using standard statistical softwares. The median ranking, as well as ranking for other quantiles, can also be estimated semiparametrically and we provide a new constrained mixed integer optimization procedure for implementation. We apply it to estimate a happiness equation using General Social Survey data of the US.

econ.EM

Analyzing Subjective Well-Being Data with Misclassification

We use novel nonparametric techniques to test for the presence of non-classical measurement error in reported life satisfaction (LS) and study the potential effects from ignoring it. Our dataset comes from Wave 3 of the UK Understanding Society that is surveyed from 35,000 British households. Our test finds evidence of measurement error in reported LS for the entire dataset as well as for 26 out of 32 socioeconomic subgroups in the sample. We estimate the joint distribution of reported and latent LS nonparametrically in order to understand the mis-reporting behavior. We show this distribution can then be used to estimate parametric models of latent LS. We find measurement error bias is not severe enough to distort the main drivers of LS. But there is an important difference that is policy relevant. We find women tend to over-report their latent LS relative to men. This may help explain the gender puzzle that questions why women are reportedly happier than men despite being worse off on objective outcomes such as income and employment.

econ.EM