Knowledge that Transforms

Abstract We propose a simple test for moment inequalities that has exact size in normal models with known variance and has uniformly asymptotically exact size under asymptotic normality. The test compares the quasi-likelihood ratio statistic to a chi-squared critical value, where the degree of freedom is the rank of the inequalities that are active in finite samples. The test requires no simulation and thus is computationally fast and especially suitable for constructing confidence sets for parameters by test inversion. It uses no tuning parameter for moment selection and yet still adapts to the slackness of the moment inequalities. Furthermore, we show how the test can be easily adapted to inference on subvectors in the common empirical setting of conditional moment inequalities with nuisance parameters entering linearly. User-friendly Matlab code to implement the test is provided.

AbstractThis article examines the optimal accumulation of capital and the effects of government debt in neoclassical growth models in which firms have market power and therefore charge prices above marginal cost. In this environment, the real interest rate earned by savers is less than the net marginal product of capital. We establish a new method for evaluating dynamic efficiency that can be applied in such economies. A plausible calibration suggests that the wedge between the real interest rate and the marginal product of capital is about 4 percentage points and that the US economy is dynamically efficient. In addition, government Ponzi schemes can have different implications for welfare than they do under competition. Even if the government can sustain a perpetual rollover of debt and accumulating interest, the policy may nonetheless reduce welfare by depressing steady-state capital and aggregate consumption. These findings suggest that even with low interest rates, as have been observed recently, fiscal policymakers should still be concerned about the crowding-out effects of government debt.

Abstract Cartels participating in procurement auctions frequently use bid rotation or prioritize incumbents to allocate contracts. However, establishing a link between observed allocation patterns and firm conduct has been difficult: there are cost-based competitive explanations for such patterns. We show that by focusing on auctions in which the winning and losing bids are very close, it is possible to distinguish allocation patterns reflecting cost differences across firms from patterns reflecting non-competitive environments. We apply our tests to two datasets: the sample of Ohio milk auctions studied in Porter and Zona (1999, “Ohio School Milk Markets: An Analysis of Bidding”, RAND Journal of Economics, 30, 263–288), and a sample of municipal procurement auctions from Japan.

Abstract We provide two characterizations, one axiomatic and the other neuro-computational, of the dependence of choice probabilities on deadlines, within the widely used softmax representation $$\beginalign* p_t\left( a,A\right) =\dfrace^\fracu\left( a\right) λ\left( t\right) +α\left( a\right) \sum_b\in Ae^\fracu\left( b\right) λ\left( t\right) +α\left( b\right) , \endalign*$$ where $p_t\left( a,A\right)$ is the probability that alternative a is selected from the set A of feasible alternatives if t is the time available to decide, λ is a time-dependent noise parameter measuring the unit cost of information, u is a time-independent utility function, and α is an alternative-specific bias that determines the initial choice probabilities (reflecting prior information and memory anchoring). Our axiomatic analysis provides a behavioural foundation of softmax (also known as Multinomial Logit Model when α is constant). Our neuro-computational derivation provides a biologically inspired algorithm that may explain the emergence of softmax in choice behaviour. Jointly, the two approaches provide a thorough understanding of softmaximization in terms of internal causes (neuro-physiological mechanisms) and external effects (testable implications).

Abstract This article studies the decentralized adoption of a technology standard when network effects are present. If the new standard is incompatible with the current installed base, adoption may be inefficiently delayed. I quantify the magnitude of “excess inertia” in the switch of the movie distribution and exhibition industries from 35 mm film to digital. I specify and estimate a dynamic game of digital hardware adoption by theatres and digital movies supply by distributors. Counterfactual simulations establish that excess inertia reduces surplus by 16% relative to the first-best adoption path; network externalities explain 41% of the surplus loss. Targeted adoption subsidies or a mandate on digital distribution help bridge this welfare gap.

Abstract We study the susceptibility of committee governance (e.g. by boards of directors), modelled as the collective determination of a ranking of a set of alternatives, to manipulation of the order in which pairs of alternatives are voted on—agenda-manipulation. We exhibit an agenda strategy called insertion sort that allows a self-interested committee chair with no knowledge of how votes will be cast to do as well as if she had complete knowledge. Strategies with this “regret-freeness” property are characterized by their efficiency, and by their avoidance of two intuitive errors. What distinguishes regret-free strategies from each other is how they prioritize among alternatives; insertion sort prioritizes lexicographically.

A concern central to the economics of privacy is that firms may use consumer data to price discriminate. A common response is that consumers should have control over their data and the ability to choose how firms access it. Since firms draw inferences based on both the data seen as well as the consumer's disclosure choices, the strategic implications of this proposal are unclear. We investigate whether such measures improve consumer welfare in monopolistic and competitive environments. We find that consumer control can guarantee gains for every consumer type relative to both perfect price discrimination and no personalized pricing. This result is driven by two ideas. First, consumers can use disclosure to amplify competition between firms. Second, consumers can share information that induces a seller---even a monopolist---to make price concessions. Furthermore, whether consumer control improves consumer surplus depends on both the technology of disclosure and the competitiveness of the marketplace. In a competitive market, simple disclosure technologies such as "track / do-not-track'' suffice for guaranteeing gains in consumer welfare. However, in a monopolistic market, welfare gains require richer forms of disclosure technology whereby consumers can decide how much information they would like to convey.

Abstract This article aims to measure and understand the role of inheritances in shaping wealth inequality. We use a quasi-experimental design and Swedish administrative data to document that the average heir depletes her inheritance within a decade while the inheritances of wealthy heirs remain intact. These different depletion rates are not due to different consumption or labour supply responses but due to different rates of return on inherited wealth. Upon their receipt, inheritances reduce relative measures of wealth inequality, such as top shares or percentile ratios. Theoretically, this reduction in inequality could be due to either a compressed inheritance distribution or similar chances of having wealthy parents (high intergenerational mobility). Empirically, the first force is more significant in Sweden. Within a decade, however, the effect is reversed: inheritances increase wealth inequality since the different depletion rates widen the inequality in inherited wealth over time. This implies that inheritance taxation can reduce long run wealth inequality only through the taxation of wealthy heirs.

Abstract We propose a method to estimate static discrete games with weak assumptions on the information available to players. We do not fully specify the information structure of the game but allow instead for all information structures consistent with players knowing their own payoffs. To make this approach tractable, we adopt as a solution concept Bayes correlated equilibrium (BCE). We characterize the sharp identified set under BCE and unrestricted equilibrium selection, and find that in simple games with limited variation in covariates identified sets are informative. In an application, we estimate a model of entry in the Italian supermarket industry and quantify the effect of large malls on local supermarkets. Estimates and predictions differ from those obtained under more restrictive assumptions.

Abstract Developing artificial intelligence (AI) technology requires data. In many domains, government data far exceed in magnitude and scope data collected by the private sector, and AI firms often gain access to such data when providing services to the state. We argue that such access can stimulate commercial AI innovation in part because data and trained algorithms are shareable across government and commercial uses. We gather comprehensive information on firms and public security procurement contracts in China’s facial recognition AI industry. We quantify the data accessible through contracts by measuring public security agencies’ capacity to collect surveillance video. Using a triple-differences strategy, we find that data-rich contracts, compared to data-scarce ones, lead recipient firms to develop significantly and substantially more commercial AI software. Our analysis suggests a contribution of government data to the rise of China’s facial recognition AI firms, and that states’ data collection and provision policies could shape AI innovation.