This chapter explains the logic of structural econometric models and compares them to other types of econometric models. We provide a framework researchers can use to develop and evaluate structural econometric models. This framework pays particular attention to describing different sources of unobservables in structural models. We use our framework to evaluate several literatures in industrial organization economics, including the literatures dealing with market power, product differentiation, auctions, regulation and entry.

Conventional hedonic techniques for estimating the value of local amenities rely on the assumption that households move freely among locations. We show that when moving is costly, the variation in housing prices and wages across locations may no longer reflect the value of differences in local amenities. We develop an alternative discrete-choice approach that models the household location decision directly, and we apply it to the case of air quality in U.S. metro areas in 1990 and 2000. Because air pollution is likely to be correlated with unobservable local characteristics such as economic activity, we instrument for air quality using the contribution of distant sources to local pollution – excluding emissions from local sources, which are most likely to be correlated with local conditions. Our model yields an estimated elasticity of willingness to pay with respect to air quality of 0.34 to 0.42. These estimates imply that the median household would pay $149 to $185 (in constant 1982-1984 dollars) for a one-unit reduction in average ambient concentrations of particulate matter. These estimates are three times greater than the marginal willingness to pay estimated by a conventional hedonic model using the same data. Our results are robust to a range of covariates, instrumenting strategies, and functional form assumptions. The findings also confirm the importance of instrumenting for local air pollution.

This paper introduces a new equilibrium framework for analyzing residential sorting, designed to take advantage of newly available restricted-access Census microdata. The framework adds an equilibrium concept to the discrete choice framework developed by McFadden (1973, 1978), permitting a more flexible characterization of preferences than has been possible in previously estimated sorting models. Using data on nearly a quarter of a million households residing in the San Francisco Bay Area in 1990, our estimates provide a precise characterization of preferences for many housing and neighborhood attributes, showing how demand for these attributes varies with a household’s income, race, education, and family structure. We use the equilibrium model in combination with these estimates to explore the effects of an increase in income inequality, the findings indicating that much of the increased spending power of the rich is absorbed by higher housing prices.

This paper specifies and estimates a dynamic model of consumer preferences for new durable goods with persistent heterogeneous consumer tastes, rational expectations about future products and repeat purchases over time. Most new consumer durable goods, particularly consumer electronics, are characterized by relatively high initial prices followed by rapid declines in prices and improvements in quality. The evolving nature of product attributes suggests the importance of modeling dynamics in estimating consumer preferences. We estimate the model on the digital camcorder industry using a panel data set on prices, sales and characteristics. We find that dynamics are a very important determinant of consumer preferences and that estimated coefficients are more plausible than with traditional static models. We use the estimates to investigate the value of new consumer goods and intertemporal elasticities of demand.

In principle, a multiproduct firm can set separate prices for all possible bundled combinations of its products (i.e., ”mixed bundling”). However, this is impractical for firms with more than a few products, because the number of prices increases exponentially with the number of products. In this study we show that simple pricing strategies are often nearly optimal—i.e., with surprisingly few prices a firm can obtain 99 % of the profit that would be earned by mixed bundling. Specifically, we show that bundle-size pricing—setting prices that depend only on the size of bundle purchased—tends to be more profitable than offering the individual products priced separately, and tends to closely approximate the profits from mixed bundling. These findings are based on an array of numerical experiments covering a broad range of demand and cost scenarios, as well as an empirical analysis of the pricing problem for an 8-product firm (a theater company).

The CPI component indices are obtained from comparing price quotes at a given store in different periods. If we omit comparisons from goods in the store in the initial, but not in the comparison, period we generate a selection bias: goods that exit are disproportionately obsolete goods that have falling prices. Building on Pakes (2003), we explain why standard hedonic predictions for second-period prices of exiting goods do not account for this bias. New hedonic methods are derived, shown to have desirable properties, and applied to three CPI samples where they generate significant selection corrections. 1 1

Since the pioneering work by Daniel McFadden in the 1970s and 1980s (McFadden, 1973, 1981, 1982, 1984) discrete (multinomial) response models based on utility maximization have become an important tool of empirical researchers. A key feature of these models is the specification of utilities associated with the alternatives in terms of choice characteristics and individual preferences. Various generalizations of the basic models have been developed to allow for heterogeneity in taste parameters and heterogeneity in product characteristics that is unobserved to the econometrician. In this paper we investigate how rich a specification of the unobserved components is needed to rationalize arbitrary patterns of choice data (generated by utility-maximizing behavior) in settings with many individual decision makers and large choice sets. We find that in general the model must include at least one unobserved choice characteristic. If, as in common, one restricts the utility function to be monotone in the unobserved choice characteristic, then up to two unobserved choice characteristics may be needed to rationalize the choice data. We illustrate the results using scanner data about yoghurt purchases, employing a Bayesian estimation strategy that is particularly well suited to dealing with multiple unobserved product characteristics. We find that the inclusion of two unobserved choice characteristics leads to more reasonable estimates of elasticities.

We present methods to estimate marginal utility and marginal product functions that are nonadditive in the unobservable random terms, using observations from a single hedonic equilibrium market. We show that nonadditive marginal utility and nonadditive marginal product functions are capable of generating equilibria that exhibit bunching, as well as other types of equilibria. We provide conditions under which these types of utility and production functions are nonparametrically identified, and we propose nonparametric estimators for them. The estimators are shown to be consistent and asymptotically normal.

We show how to nonparametrically identify the distribution of heterogeneity in a general class of structural economic choice models. We state an economic property known as reducibility and prove that reducibility ensures identification. Reducibility makes verifying the identification of nonlinear models a straightforward task because it is a condition that is stated directly in terms of a choice model. We can allow for a nonparametric distribution over nonparametric functions of the data. We use our framework to prove identification in three classes of economic models: 1) nonparametric regressions including with endogenous regressors, 2) multinomial discrete choice including endogenous regressors as well as multiple purchases with complementarities, and 3) selection and mixed continuous-discrete choice. Our identification strategy avoids identification at infinity. For selection, we allow for essential heterogeneity in both the selection and outcome equations and fully identify the joint distribution of outcomes.

Catherine Thomas, and Olivier Toubia for their comments on previous drafts and to Dan