Knowledge that Transforms

In many markets, goods flow from initial producers to final customers travelling through many layers of intermediaries and information is asymmetric. We study a dynamic model of bargaining in networks that captures these features.We show that the equilibrium price demanded over time is non-monotonic, but the sequence of transaction prices declines over time, with the possible exception of the last period. The price dynamic is, therefore, reminiscent of fire-sales and hot-potato trading. Traders who intermediate the object arise endogenously and make a positive profit. The profit-earning intermediaries are not necessarily traders with many connections; for the case of multilayer networks, they belong to the path that reaches the maximum number of potential buyers using the minimal number of intermediaries. This is not necessarily the path of the network that maximizes the probability of consumption by traders who value the most the object (i.e. welfare).

We study a principal–agent setting in which both sides learn about future profitability from output, and the project can be abandoned/terminated if profitability is too low. With learning, shirking by the agent both reduces output and lowers the principal’s estimate of future profitability. The agent can exploit this belief discrepancy and earn information rents, reducing his incentives to exert effort. The optimal contract controls information rents to improve incentives by distorting the termination decision. Our results capture the transition from a young, financially constrained firm to a mature firm that pays dividends. For young firms, poor performance permanently raises the termination threshold, as doing so lowers information rents. Mature firms pay smoothed dividends and have a fixed termination threshold. Dividend smoothing occurs because earnings surprises are used to adjust financial slack in line with profitability. When profitability only reflects the agent’s private ability, a simple equity contract is optimal.

Media outlets are increasingly owned by conglomerates, inducing a conflict of interest: a media outlet can bias its coverage to benefit companies in the same group. We test for bias by examining movie reviews in media outlets owned by News Corp, such as the Wall Street Journal, and Time Warner, such as Time. We find higher ratings for 20th Century Fox movies in News Corp. outlets compared to movies by other studios. To disentangle bias from correlation of taste, we introduce and validate a novel matching procedure using individual movie ratings from online platforms. Using this procedure, we find no evidence of bias in News Corp. nor Time Warner outlets. We reject even small effects, such as bias of one extra star (out of four) every thirteen movies. We test for differential bias when the return to bias is plausibly higher, examine bias by media outlet and by journalist, as well as editorial bias. We also consider bias by omission—whether media outlets are more likely to review highly-rated movies by affiliated studios—and conflict of interest within a movie aggregator. In none of these dimensions do we find evidence of bias. We relate to previous work and discuss three explanations for the lack of bias in our setting: high values of media reputation, organizational features in a conglomerate, and low returns to bias.

While neoclassical theory emphasizes the impact of trade on wage inequality between occupations and sectors, more recent theories of firm heterogeneity point to the impact of trade on wage dispersion within occupations and sectors. Using linked employer–employee data for Brazil, we show that much of overall wage inequality arises within sector–occupations and for workers with similar observable characteristics; this within component is driven by wage dispersion between firms; and wage dispersion between firms is related to firm employment size and trade participation. We then extend the heterogenous-firm model of trade and inequality from Helpman et al. (2010) and estimate it with Brazilian data. We show that the estimated model provides a close approximation to the observed distribution of wages and employment. We use the estimated model to undertake counterfactuals, in which we find sizable effects of trade on wage inequality.

Does fiscal policy stimulate output? Structural vector autoregressions have been used to address this question, but no stylized facts have emerged. This paper makes two contributions. First, I derive analytical relationships between the output elasticities of tax revenue and government expenditures, and fiscal multipliers. I show that different priors about elasticities implied by the identification schemes generate a large dispersion in the estimates of tax and spending multipliers. Second, I estimate fiscal multipliers consistent with prior distributions of the elasticities computed by a variety of empirical strategies, and by employing a simple dynamic stochastic general equilibrium model. I document three findings for the U.S. for the period 1947-2010. First, the impact tax multiplier is close to 0. Second, the impact spending multiplier ranges between 0.35 and 1. Third, the probability that the spending multiplier is larger than the tax multiplier is above 0.8, for up to four years after policy interventions.

When designing data collection, crucial questions arise regarding how much data to collect and how much effort to expend to enhance the quality of the collected data. To make choice of sample design a coherent subject of study, it is desirable to specify an explicit decision problem. We use the Wald framework of statistical decision theory to study allocation of a budget between two or more sampling processes. These processes all draw random samples from a population of interest and aim to collect data that are informative about the sample realizations of an outcome. They differ in the cost of data collection and the quality of the data obtained. One may incur lower cost per sample member but yield lower data quality than another. Increasing the allocation of budget to a low-cost process yields more data, while increasing the allocation to a high-cost process yields better data. We initially view the concept of “better data” abstractly and then fix attention on two important cases. In both cases, a high-cost sampling process accurately measures the outcome of each sample member. The cases differ in the data yielded by a low-cost process. In one, the low-cost process has non-response and in the other it provides a low-resolution interval measure of each sample member’s outcome. In these settings, we study minimax-regret sample design for prediction of a real-valued outcome under square loss; that is, design which minimizes maximum mean square error. The analysis imposes no assumptions that restrict the unobserved outcomes. Hence, the decision maker must cope with both the statistical imprecision of finite samples and the partial identification of the true state of nature.

This study incorporates a recent preference specification of expectations-based loss aversion, which has been applied broadly in microeconomics, into a classic macro model to offer a unified explanation for three empirical observations about life-cycle consumption. First, loss aversion explains excess smoothness and sensitivity—that is, the empirical observation that consumption responds to income shocks with a lag. Intuitively, such lagged responses allow the agent to delay painful losses in consumption until his expectations have adjusted. Secondly, the preferences generate a hump-shaped consumption profile. Early in life, consumption is low due to a first-order precautionary-savings motive. However, as uncertainty resolves over time, this motive is dominated by time-inconsistent overconsumption that eventually leads to declining consumption towards the end of life. Thirdly, consumption drops at retirement. Prior to retirement, the agent wants to overconsume his uncertain income before his expectations catch up. Post-retirement, however, income is no longer uncertain, and overconsumption is associated with a sure loss in future consumption. As an empirical contribution, I structurally estimate the preference parameters using life-cycle consumption data. My estimates match those obtained in experiments and other micro studies, and generate the degree of excess smoothness observed in macro consumption data.

I provide an analysis of vertical relations in markets with imperfect competition at both layers of the supply chain and where exchange is intermediated either with wholesale prices or revenue-sharing contracts. Revenue-sharing is extremely attractive to firms that are able to set the revenue shares but often makes the firms that set retail prices worse off. This is so whether revenue-sharing lowers or raises industry profits. These results are strengthened when a market moves from “the wholesale model” of sales to “the agency model” of sales, which results in retailers setting revenue shares and suppliers setting retail prices. I also show that retail price-parity restrictions raise industry prices. These results provide a potential explanation for why many online retailers have adopted the agency model and retail price-parity clauses.

Using a new narrative measure of fiscal policy shocks for the U.K., we show that households with mortgage debt exhibit large and significant consumption responses to tax changes. Homeowners without a mortgage, in contrast, do not adjust their expenditure, with responses not statistically different from zero at all horizons. We compare our findings to the predictions of traditional and newer theories of liquidity constraints, providing a novel interpretation for the aggregate effects of tax changes on the macroeconomy.

This paper investigates how legal cannabis access affects student performance. Identification comes from an exceptional policy introduced in the city of Maastricht in the Netherlands that discriminated access via licensed cannabis shops based on an individual’s nationality. We apply a difference-in-difference approach using administrative panel data on course grades of local students enrolled at Maastricht University before and during the partial cannabis prohibition. We find that the academic performance of students who are no longer legally permitted to buy cannabis substantially increases. Grade improvements are driven by younger students and the effects are stronger for women and low performers. In line with how cannabis consumption affects cognitive functioning, we find that performance gains are larger for courses that require more numerical/mathematical skills. Our investigation of underlying channels using course evaluations suggests that performance gains are driven by an improved understanding of the material rather than changes in students’ study effort.