Nonparametric Identification of Multinomial Choice Demand Models with Heterogeneous Consumers

We consider identification of nonparametric random utility models of multinomial choice using "micro data," i.e., observation of the characteristics and choices of individual consumers. Our model of preferences nests random coefficients discrete choice models widely used in practice with parametric functional form and distributional assumptions. However, the model is nonparametric and distribution free. It allows choice-specific unobservables, endogenous choice characteristics, unknown heteroskedasticity, and high-dimensional correlated taste shocks. Under standard "large support" and instrumental variables assumptions, we show identifiability of the random utility model. We demonstrate robustness of these results to relaxation of the large support condition and show that when it is replaced with a weaker "common choice probability" condition, the demand structure is still identified. We show that key maintained hypotheses are testable.Nonparametric identification, Discrete choice demand, Differentiated products

Identification in a Class of Nonparametric Simultaneous Equations Models

We consider identification in a class of nonseparable nonparametric simultaneous equations models introduced by Matzkin (2008). These models combine standard exclusion restrictions with a requirement that each structural error enter through a "residual index" function. We provide constructive proofs of identification under several sets of conditions, demonstrating tradeoffs between restrictions on the support of the instruments, restrictions on the joint distribution of the structural errors, and restrictions on the form of the residual index function.Simultaneous equations, Nonseparable models, Nonparametric identification

Identification of a Heterogeneous Generalized Regression Model with Group Effects

We consider identification in a "generalized regression model" (Han, 1987) for panel settings in which each observation can be associated with a "group" whose members are subject to a common unobserved shock. Common examples of groups include markets, schools or cities. The model is fully nonparametric and allows for the endogeneity of group-specific observables, which might include prices, policies, and/or treatments. The model features heterogeneous responses to observables and unobservables, and arbitrary heteroskedasticity. We provide sufficient conditions for full identification of the model, as well as weaker conditions sufficient for identification of the latent group effects and the distribution of outcomes conditional on covariates and the group effect.Nonparametric identification, Binary choice, Threshold crossing, Censored regression, Proportional hazard model

Nonparametric Identification of Differentiated Products Demand Using Micro Data

We examine identification of differentiated products demand when one has “micro data” linking the characteristics and choices of individual consumers. Our model nests standard specifications featuring rich observed and unobserved consumer heterogeneity as well as product/market-level unobservables that introduce the problem of econometric endogeneity. Previous work establishes identification of such models using marketlevel data and instruments for all prices and quantities. Micro data provides a panel structure that facilitates richer demand specifications and reduces requirements on both the number and types of instrumental variables. We address identification of demand in the standard case in which non-price product characteristics are assumed exogenous, but also cover identification of demand elasticities and other key features when these product characteristics are endogenous and not instrumented. We discuss implications of these results for applied work

Identification of Nonparametric Simultaneous Equations Models with a Residual Index Structure

We present new identification results for a class of nonseparable nonparametric simultaneous equations models introduced by Matzkin (2008). These models combine traditional exclusion restrictions with a requirement that each structural error enter through a “residual index.” Our identification results are constructive and encompass a range of special cases with varying demands on the exogenous variation provided by instruments and the shape of the joint density of the structural errors. The most important of these results demonstrate identification even when instruments have limited variation. A genericity result demonstrates a formal sense in which the associated density conditions may be viewed as mild, even when instruments vary only over a small open ball

Identification in Differentiated Products Markets

Empirical models of demand for — and, often, supply of — differentiated products are widely used in practice, typically employing parametric functional forms and distributions of consumer heterogeneity. We review some recent work studying identification in a broad class of such models. This work shows that parametric functional forms and distributional assumptions are not essential for identification. Rather, identification relies primarily on the standard requirement that instruments be available for the endogenous variables — here, typically, prices and quantities. We discuss the kinds of instruments needed for identification and how the reliance on instruments can be reduced by nonparametric functional form restrictions or better data. We also discuss results on discrimination between alternative models of oligopoly competition

Identification of Nonparametric Simultaneous Equations Models with a Residual Index Structure

We present new results on the identifiability of a class of nonseparable nonparametric simultaneous equations models introduced by Matzkin (2008). These models combine exclusion restrictions with a requirement that each structural error enter through a “residual index.” Our identification results encompass a variety of special cases allowing tradeoffs between the exogenous variation required of instruments and restrictions on the joint density of structural errors. Among these special cases are results avoiding any density restriction and results allowing instruments with arbitrarily small support

Foundations of Demand Estimation

Demand elasticities and other features of demand are critical determinants of the answers to most positive and normative questions about market power or the functioning of markets in practice. As a result, reliable demand estimation is an essential input to many types of research in Industrial Organization and other fields of economics. This chapter presents a discussion of some foundational issues in demand estimation. We focus on the distinctive challenges of demand estimation and strategies one can use to overcome them. We cover core models, alternative data settings, common estimation approaches, the role and choice of instruments, and nonparametric identification

Financial Performance Analysis of Selected Commercial Banks in Ethiopia

Accounting data are useful in assessing the economic prospects of a firm. The paper shows how financial ratios can be used to explore the sources of a firm’s profitability and evaluate the “quality” of its earnings in a systematic fashion. Hence, the aim of the study is to analyze the financial performance of commercial banks in Ethiopia for the period between 2009 and 2012.A sample of the top seven commercial banks was selected based on the value of their total assets at the end of the 2009 financial year. These are the banks that dominate the sector with the top 7 banks controlling 90.4% of the total industry assets which makes them systemically important banks The results of the study indicated that CBE showed the highest level of RoE all the time but this was driven by its high leverage levels. Moreover, all banks were found to be unduly liquid affecting their revenue generating capacity. This is partly because of government imposed loan restriction. Dashen Bank has continuously improved its performance throughout the study period in most of the parameters used to measure its performance. Wegagen Bank had the most stable earnings over time as a result of its policy to use high level of equity financing. For a sustained good banking performance in the country, it is recommended that the banks invest more in interest bearing assets, mainly loans, to fully utilize their revenue generating capacity. The Ethiopian government is also recommended to balance its desire to control inflation with the need to maintain lasting viability of the banking industry.Keywords: Ratio analysis, financial performance, Bank performance, Ethiopi