When Does Advice Impact Startup Performance? -- by Aaron Chatterji, Solene Delecourt, Sharique Hasan, Rembrand M. Koning
Why do some entrepreneurs thrive while others fail? We explore whether the advice entrepreneurs receive about people management influences their firm's performance. We conducted a randomized field experiment in India with 100 high-growth technology firms whose founders received in-person advice from other entrepreneurs who varied in their managerial style. We find that entrepreneurs who received advice from peers with an active approach to managing people-instituting regular meetings, setting goals consistently, and providing frequent feedback to employees-grew 28% larger and were 10 percentage points less likely to fail than those who got advice from peers with a passive people-management approach two years after our intervention. Entrepreneurs with MBAs or accelerator experience did not respond to this intervention, suggesting that formal training can limit the spread of peer advice.
Job Tasks and the Gender Wage Gap among College Graduates -- by Todd R. Stinebrickner, Ralph Stinebrickner, Paul J. Sullivan
Gender differences in current and past job tasks may be crucial for understanding the gender wage gap. We use novel task data to address well-known measurement concerns, including that standard task measures assume away within-occupation gender differences in tasks. We find that unique measures of task-specific experience, in particular high-skilled information experience, are of particular importance for understanding the substantial widening of the wage gap early in the career. Highlighting the importance of these measures, traditional work-related proxies for gender differences in human capital accumulation are not informative because general work experience is similar by gender for our recent graduates.
A large literature demonstrates that occupational licensing is a labor market friction that distorts labor supply allocation and prices. We show that an occupational license serves as a job market signal, similar to education. In the presence of occupational licensing, we find evidence that firms rely less on observable characteristics such as race and gender in determining employee wages. As a result, licensed minorities and women experience smaller wage gaps than their unlicensed peers.
Banks, Insider Connections, and Industrialization in New England: Evidence from the Panic of 1873 -- by Eric Hilt
This paper studies the role of bank affiliations in mitigating frictions related to asymmetric information. The analysis focuses on Massachusetts, and tests whether firms with bank directors on their boards fared better following the Panic of 1873, which did not directly impact the state's commercial banks, but produced a prolonged economic slump. Around 59 percent of all non-financial corporations in the state had a bank director on their board in 1872. These firms survived the recession of the 1870s at higher rates, grew faster and experienced less of a deterioration in their credit ratings. Consistent with banker-directors helping to resolve problems related to asymmetric information, these effects were strongest among young firms. Counterfactual estimates suggest that in the absence of bank affiliations, the total assets of the non-financial corporations in Massachusetts that existed in 1872 would have been 35 percent lower in the wake of the recession. These results suggest an important role for the banking sector in New England's industrialization, namely that affiliations with commercial banks helped nonfinancial corporations maintain access to external finance during economic downturns.
Patenting in software, cloud computing, and artificial intelligence has grown rapidly in recent years. Such patents are acquired primarily by large US technology firms such as IBM, Microsoft, Google, and HP, as well as by Japanese multinationals such as Sony, Canon, and Fujitsu. Chinese patenting in the US is small but growing rapidly, and world-leading for drone technology. Patenting in machine learning has seen exponential growth since 2010, although patenting in neural networks saw a strong burst of activity in the 1990s that has only recently been surpassed. In all technological fields, the number of patents per inventor has declined near-monotonically, except for large increases in inventor productivity in software and semiconductors in the late 1990s. In most high-tech fields, Japan is the only country outside the US with significant US patenting activity; however, whereas Japan played an important role in the burst of neural network patenting in the 1990s, it has not been involved in the current acceleration. Comparing the periods 1970-89 and 2000-15, patenting in the current period has been primarily by entrant assignees, with the exception of neural networks.
The question of how firms build market share matters for firm dynamics, business cycles, international trade, and industrial organization. Using Nielsen Retail Scanner data for the United States, we document that in the consumer food industry, brands experience substantial growth in market share in the first four years after successful entry into a regional market. However, markups are flat with respect to brand tenure. This finding is at odds with a large literature on customer markets which argues that firms acquire customers by temporarily offering low markups, and later raise markups once customers are locked in. However, it is consistent with a literature which emphasizes the importance of marketing and advertising activities for building market share.
Common Values, Unobserved Heterogeneity, and Endogenous Entry in U.S. Offshore Oil Lease Auction -- by Giovanni Compiani, Philip Haile, Marcelo Sant'Anna
An oil lease auction is the classic example motivating a common values model. However, formal testing for common values has been hindered by unobserved auction-level heterogeneity, which is likely to affect both participation in an auction and bidders' willingness to pay. We develop and apply an empirical approach for first-price sealed bid auctions with affiliated values, unobserved heterogeneity, and endogenous bidder entry. The approach also accommodates spatial dependence and sample selection. Following Haile, Hong and Shum (2003), we specify a reduced form for bidder entry outcomes and rely on an instrument for entry. However, we relax their control function requirements and demonstrate that our specification is generated by a fully specified game motivated by our application. We show that important features of the model are nonparametrically identified and propose a semiparametric estimation approach designed to scale well to the moderate sample sizes typically encountered in practice. Our empirical results show that common values, affiliated private information, and unobserved heterogeneity--three distinct phenomena with different implications for policy and empirical work--are all present and important in U.S. offshore oil and gas lease auctions. We find that ignoring unobserved heterogeneity in the empirical model obscures the presence of common values. We also examine the interaction between affiliation, the winner's curse, and the number of bidders in determining the aggressiveness of bidding and seller revenue
Detecting Urban Markets with Satellite Imagery: An Application to India -- by Kathryn Baragwanath Vogel, Ran Goldblatt, Gordon H. Hanson, Amit K. Khandelwal
This paper proposes a methodology for defining urban markets based on economic activity detected by satellite imagery. We use nighttime lights data, whose use in economics is increasingly common, to define urban markets based on contiguous pixels that have a minimum threshold of light intensity. The coarseness of the nightlight data and the blooming effect of lights, however, create markets whose boundaries are too expansive and too smooth relative to the visual inspection of actual cities. We compare nightlight-based markets to those formed using high-resolution daytime satellite imagery, whose use in economics is less common, to detect the presence of builtup landcover. We identify an order of magnitude more markets with daytime imagery; these markets are realistically jagged in shape and reveal much more within and across-market variation in the density of economic activity. The size of landcover-based markets displays a sharp sensitivity to the proximity of paved roads that is not present in the case of nightlight-based markets. Our results suggest that daytime satellite imagery is a promising source of data for economists to study the spatial extent and distribution of economic activity.
What is the role of structural estimation in behavioral economics? I discuss advantages, and limitations, of the work in Structural Behavioral Economics. I also cover common modeling choices and how to get started. Among the advantages, I argue that structural estimation builds on, and expands, a classical behavioral tool, simple calibrations, and that it benefits from the presence of a few parsimonious behavioral models which can be taken to the data. Estimation is also well suited for experimental work, common in behavioral economics, as it can lead to improvements in the experimental design. In addition, at a time where policy implications of behavioral work are increasingly discussed, it is important to ground these policy implications in (estimated) models. Structural work, however, has important limitations, which are relevant to its behavioral applications. Estimation takes much longer and the extra degree of complexity can make it difficult to know which of a series of assumptions is driving the results. For related reasons, it is also easy to over-reach with the welfare implications. Taking this into account, I provide a partial how-to guide to structural behavioral economics, covering: (i) the choice of estimation method; (ii) the modeling of heterogeneity; (iii) identification and sensitivity. Finally, I discuss common issues for the estimation of leading behavioral models. I illustrate this discussion with selected coverage of existing work in the literature.
By downplaying externalities, magnifying the cost of moral behavior, or suggesting not being pivotal, exculpatory narratives can allow individuals to maintain a positive image when in fact acting in a morally questionable way. Conversely, responsibilizing narratives can help sustain better social norms. We investigate when narratives emerge from a principal or the actor himself, how they are interpreted and transmitted by others, and when they spread virally. We then turn to how narratives compete with imperatives (general moral rules or precepts) as alternative modes of communication to persuade agents to behave in desirable ways.
This paper reviews recent economic research in tax compliance and enforcement. After briefly laying out the economics of tax evasion, it focuses on recent empirical contributions. It first discusses what methodologies and data have facilitated these contributions, and then presents critical summaries of what has been learned. It discusses a promising new development, the analysis of randomized controlled trials mostly delivered via letters from the tax authority, and then reviews recent research using various methods about the impact of the principal enforcement tax policy instruments: audits, information reporting, and remittance regimes. I also explore several understudied issues worthy of more research attention. The paper closes by outlining a normative framework based on the behavioral response elasticities now being credibly estimated that allows one to assess whether a given enforcement intervention is worth doing.
We study the welfare costs of markups in a dynamic model with heterogeneous firms and endogenously variable markups. We find that the welfare costs of markups are large. We decompose the costs of markups into three channels: (i) an aggregate markup that acts like a uniform output tax, (ii) misallocation of factors of production, and (iii) an inefficiently low rate of entry. We find that the aggregate markup accounts for about two-thirds of the costs, misallocation accounts for about one-third, and the costs due to inefficient entry are negligible. We evaluate simple policies aimed at reducing the costs of markups. Subsidizing entry is not an effective tool in our model: while more competition reduces individual firms' markups it also reallocates market shares towards larger firms and the net effect is that the aggregate markup hardly changes. Size-dependent policies aimed at reducing concentration can reduce the aggregate markup but have the side effect of greatly increasing misallocation and reducing aggregate productivity.