|
on Discrete Choice Models |
| By: | Le-Yu Chen (Institute for Fiscal Studies and Academia Sinica); Sokbae Lee (Institute for Fiscal Studies and Columbia University and IFS) |
| Abstract: | This paper studies inference of preference parameters in semiparametric discrete choice models when these parameters are not point-identifi ed and the identifi ed set is characterized by a class of conditional moment inequalities. Exploring the semiparametric modeling restrictions, we show that the identi fied set can be equivalently formulated by moment inequalities conditional on only two continuous indexing variables. Such formulation holds regardless of the covariate dimension, thereby breaking the curse of dimensionality for nonparametric inference based on the underlying conditional moment inequalities. We further apply this dimension reducing characterization approach to the monotone single index model and to a variety of semiparametric models under which the sign of conditional expectation of a certain transformation of the outcome is the same as that of the indexing variable. |
| Keywords: | partial identi fication, conditional moment inequalities, discrete choice, monotone single index model, curse of dimensionality |
| JEL: | C14 C25 |
| Date: | 2017–11–22 |
| URL: | http://d.repec.org/n?u=RePEc:ifs:cemmap:51/17&r=dcm |
| By: | Victor Chernozhukov (Institute for Fiscal Studies and MIT); Ivan Fernandez-Val (Institute for Fiscal Studies and Boston University); Whitney K. Newey (Institute for Fiscal Studies and MIT) |
| Abstract: | Multinomial choice models are fundamental for empirical modeling of economic choices among discrete alternatives. We analyze identification of binary and multinomial choice models when the choice utilities are nonseparable in observed attributes and multidimensional unobserved heterogeneity with cross-section and panel data. We show that derivatives of choice probabilities with respect to continuous attributes are weighted averages of utility derivatives in cross-section models with exogenous heterogeneity. In the special case of random coefficient models with an independent additive effect, we further characterize that the probability derivative at zero is proportional to the population mean of the coefficients. We extend the identification results to models with endogenous heterogeneity using either a control function or panel data. In time stationary panel models with two periods, we find that differences over time of derivatives of choice probabilities identify utility derivatives "on the diagonal," i.e. when the observed attributes take the same values in the two periods. We also show that time stationarity does not identify structural derivatives "off the diagonal" both in continuous and multinomial choice panel models. |
| Keywords: | Multinomial choice, binary choice, nonseparable model, random coefficients, panel data, control function. |
| Date: | 2017–06–27 |
| URL: | http://d.repec.org/n?u=RePEc:ifs:cemmap:33/17&r=dcm |
| By: | Richard Freeman; Wenquan Liang; Ran Song; Christopher Timmins |
| Abstract: | We develop a residential sorting model incorporating migration disutility to recover the implicit value of clean air in China. The model is estimated using China Population Census Data along with PM2.5 satellite data. Our study provides new evidence on the willingness to pay for air quality improvement in developing countries and is the first application of an equilibrium sorting model to the valuation of non-market amenities in China. We employ two novel instrumental variables based on coal-fired electricity generation and wind direction to address the endogeneity of local air pollution. Results suggest important differences between the residential sorting model and a conventional hedonic model, highlighting the role of moving costs and the discreteness of the choice set. Our sorting results indicate that the economic value of air quality improvement associated with a one-unit decline in PM2.5 concentration is up to $8.83 billion for all Chinese households in 2005. |
| JEL: | Q51 Q53 R23 |
| Date: | 2017–12 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:24157&r=dcm |
| By: | Kalouptsidi, Myrto; Scott, Paul; Souza-Rodrigues, Eduardo |
| Abstract: | Dynamic discrete choice models (DDC) are not identified nonparametrically. However, the non-identification of DDC models does not necessarily imply non-identification of coun- terfactuals of interest. Using a novel approach that can accommodate both nonparametric and restricted payoff functions, we provide necessary and sufficient conditions for the iden- tification of counterfactual behavior and welfare for a broad class of counterfactuals. The conditions are simple to check and can be applied to virtually all counterfactuals in the DDC literature. To explore the robustness of counterfactual results to model restrictions in practice, we consider a numerical example of a monopolist's entry problem, as well as an empirical model of agricultural land use. In each case, we provide examples of both identified and non-identified counterfactuals of interest. |
| Keywords: | counterfactual; dynamic discrete choice; identification; welfare |
| Date: | 2017–11 |
| URL: | http://d.repec.org/n?u=RePEc:cpr:ceprdp:12470&r=dcm |