Resource misallocation can lower aggregate total factor productivity (TFP).We
use microdata on manufacturing establishments to quantify the potential extent
of misallocation in China and India versus the United States. We measure sizable
gaps in marginal products of labor and capital across plants within narrowly
defined industries in China and India compared with the United States. When
capital and labor are hypothetically reallocated to equalize marginal products to
the extent observed in the United States, we calculate manufacturing TFP gains
of 30%–50% in China and 40%–60% in India.

/pdf/misallocation-and-manufacturing-tfp-in-china-and-india-2iv0rc70q7.pdf

Misallocation and Manufacturing TFP in China and India

This article examines how product and consumer characteristics moderate the influence of online consumer reviews on product sales using data from the video game industry. The findings indicate that online reviews are more influential for less popular games and games whose players have greater Internet experience. The article shows differential impact of consumer reviews across products in the same product category and suggests that firms' online marketing strategies should be contingent on product and consumer characteristics. The authors discuss the implications of these results in light of the increased share of niche products in recent years.

/pdf/impact-of-online-consumer-reviews-on-sales-the-moderating-53shopqfp1.pdf

Impact of Online Consumer Reviews on Sales: The Moderating Role of Product and Consumer Characteristics

We propose a more complete conceptual framework for analysis of SME credit availability issues. In this framework, lending technologies are the key conduit through which government policies and national financial structures affect credit availability. We emphasize a causal chain from policy to financial structures, which affect the feasibility and profitability of different lending technologies. These technologies, in turn, have important effects on SME credit availability. Financial structures include the presence of different financial institution types and the conditions under which they operate. Lending technologies include several transactions technologies plus relationship lending. We argue that the framework implicit in most of the literature is oversimplified, neglects key elements of the chain, and often yields misleading conclusions. A common oversimplification is the treatment of transactions technologies as a homogeneous group, unsuitable for serving informationally opaque SMEs, and a frequent misleading conclusion is that large institutions are disadvantaged in lending to opaque SMEs.

/pdf/a-more-complete-conceptual-framework-for-sme-finance-4xac6ul2wa.pdf

A more complete conceptual framework for SME finance

The ready-to-eat cereal industry is characterized by high concentration, high price-cost margins, large advertising-to-sales ratios, and numerous introductions of new products. Previous researchers have concluded that the ready-to-eat cereal industry is a classic example of an industry with nearly collusive pricing behavior and intense nonprice competition. This paper empirically examines this conclusion. In particular, I estimate price-cost margins, but more importantly I am able empirically to separate these margins into three sources: (i) that which is due to product differentiation; (ii) that which is due to multi-product firm pricing; and (iii) that due to potential price collusion. The results suggest that given the demand for different brands of cereal, the first two effects explain most of the observed price-cost margins. I conclude that prices in the industry are consistent with noncollusive pricing behavior, despite the high price-cost margins. Leading firms are able to maintain a portfolio of differentiated products and influence the perceived product quality. It is these two factors that lead to high price-cost margins.

/pdf/measuring-market-power-in-the-ready-to-eat-cereal-industry-1gg1mz66vx.pdf

Measuring Market Power in the Ready-to-Eat Cereal Industry

The ready-to-eat cereal industry is characterized by high concentration margins, large advertising to sales ratios, and numerous introductions of new products. Previous researchers have concluded that the ready-to-eat cereal industry is a classic example of an industry with nearly collusive pricing behavior and intense non-price competition. This paper empirically examines this conclusion. In particular, I estimate price-cost margins importantly I am able empirically to separate these margins into three parts: (1) that which is due to product differentiation; (2) that which is due to multi-product firm pricing; and (3) that due to potential price collusion. The results suggest that given the demand for different brands of cereal, the first two effects explain most of the observed price-cost markups. I conclude that prices in the industry are consistent with non-collusive pricing behavior to maintain a portfolio of differentiated products influence the perceived quality of these products, and it is these two factors that lead to high price-cost margins.

Adverse selection is perceived to be a major source of market failure in insurance markets. There is little empirical evidence on the extent of the problem. We estimate a structural model of health insurance and health care choices using data on single individuals from the NMES. A robust prediction of adverse-selection models is that riskier types buy more coverage and, on average, end up using more care. We test for unobservables linking health insurance status and health care consumption. We find no evidence of informational asymmetries.

https://www.jstor.org/stable/pdfplus/2696362.pdf

Asymmetric information in health insurance: evidence from the National Medical Expenditure Survey.

Temporary price reductions (sales) are common for many goods and naturally result in large increases in the quantity sold. Demand estimation based on temporary price reductions may mismeasure the long-run responsiveness to prices. In this paper we quantify the extent of the problem and assess its economic implications. We structurally estimate a dynamic model of consumer choice using two years of scanner data on the purchasing behavior of a panel of households. The results suggest that static demand estimates, which neglect dynamics, (i) overestimate own-price elasticities by 30 percent, (ii) underestimate cross-price elasticities by up to a factor of 5, and (iii) overestimate the substitution to the no-purchase or outside option by over 200 percent. This suggests that policy analysis based on static elasticity estimates will underestimate price-cost margins and underpredict the effects of mergers.

/pdf/measuring-the-implications-of-sales-and-consumer-inventory-1r2fnmo0cb.pdf

Measuring the Implications of Sales and Consumer Inventory Behavior

This paper develops a multiple-discrete choice model for the analysis of demand of differentiated products. Users maximize profits by choosing the number of units of each brand they purchase. Multiple-unit as well as multiple-brand purchases are allowed. These two features distinguish this model from classical discrete choice models which consider only a single choice among mutually exclusive alternatives. Model parameters are estimated using the simulated method of moments technique. Both requirements - microfoundations and estimability -are imposed in order to exploit the available micro level data on personal computer purchases. The estimated demand structure is used to assess welfare gains from computerization and technological innovation in peripherals industries. The estimated return on investment in computers is 90%. Moreover, a 10% increase in the performance to price ratio of microprocessors leads to a 4% gain in the estimated end user surplus.

Estimating Multiple-Discrete Choice Models: An Application to Computeri-Zzation Returns

Temporary price reductions (sales) are common for many goods and naturally result in a large increase in the quantity sold. We explore whether the data support the hypothesis that these increases are, at least partly, due to demand anticipation: at low prices, consumers store for future consumption. This effect, if present, has broad economic implications. We test the predictions of an inventory model using scanner data with two years of household purchases. The results are consistent with an inventory model and suggest that static demand estimates may overestimate price sensitivity.

/pdf/sales-and-consumer-inventory-12dcb16fsw.pdf

Sales and Consumer Inventory

Buyers in many markets face multiple-discrete choices: they can purchase multiple-units as well as multiple-brands at the same time. This paper presents a multiple-discrete choice model for the analysis of differentiated products demand. Users maximize profits by choosing the number of units of each brand they purchase. I estimate the model using micro-level data on the demand for personal computers. I use the estimated demand structure to assess the welfare gains from computerization and technological innovation in peripherals. The estimated return on investment in personal computers is 92%. Moreover, a 10% increase in the performance-to-price ratio of microprocessors leads to a 2.2% gain in the estimated user surplus. The personal computer (PC) market is of interest to industrial organization economists because of its size, the continual technological change, and above all, because of the farreaching implications of PCs on the economy as a whole. Several distinct features make PC demand difficult to model. PCs are a differentiated durable good in constant technological evolution. Moreover, buyers make multiple-discrete choices. Firms, according to our data, spread their purchases of PCs over different brands. At the same time they buy PCs in blocks, several units of each brand that they have chosen. The aim of the paper is to present a model that captures these features and to use this model to estimate the welfare gains from computerization. Classical discrete choice models allow one choice among mutually exclusive alternatives. In contrast, the proposed framework allows users to demand multiple units and multiple brands. The model can be applied to other cases of multiple-discrete choices. e.g. the composition of airline fleets, car holdings per household, the fields of the faculty in economics departments, household cereals consumption, or any other good consumed in more than one variety during a relevant time period. Although pervasive, multiple-discrete choice problems have received little attention because of their complexity. A central issue regarding the PC market is the current controversy in the economics literature about the "computerization puzzle". This puzzle stems from the empirical finding that computerization has had no effect on firm productivity (Griliches and Siegel (1991) and Morrison and Berndt (1990)). Contrary to those results, Hendel (1994) and Lichtenberg (1995), using more disaggregate data than most previous studies, report excess returns to computerization. This indicates that data aggregation may have created the computerization puzzle. In this paper, I present a model consistent with the basic

/pdf/estimating-multiple-discrete-choice-models-an-application-to-1pvkjgcqz0.pdf

Igal Hendel

Papers

Asymmetric information in health insurance: evidence from the National Medical Expenditure Survey.

Measuring the Implications of Sales and Consumer Inventory Behavior

Estimating Multiple-Discrete Choice Models: An Application to Computeri-Zzation Returns

Sales and Consumer Inventory

Estimating multiple-discrete choice models: An application to computerization returns