We examine the influence of both organizational and geographical religiosity, as important ethical parameters moderating a bank’s decision to securitize their assets. The study employs a unique database of banks located within countries marked by high (low) religious adherence. Our results provide evidence that different measures of religiosity affect a bank’s decision to securitize their assets: Banks located in countries with high religious adherence are less likely to engage with securitization compared to banks in countries with lower religiosity, while Islamic banks have a higher likelihood of embarking on a highly monitored model of asset securitization in contrast to conventional banks. When examining the motives underlying a bank’s decision to securitize assets, there is strong evidence that Islamic banks securitize their assets to improve their portfolio diversification, financial performance, and regulatory compliance. This study highlights the importance of considering informal ethical mechanisms, such as religiosity, at both the country and firm levels, when studying bank risk-taking and trading decisions, especially in countries with dual banking systems.

Abstract How do barriers to the diffusion of academic research affect innovation? In 2008, the National Institutes of Health (NIH) mandated free online availability of funded research. This policy caused a 50 percentage point increase in free access to funded articles. We introduce a novel measure, in-text patent citations, to study how this mandate affected industry use of academic science. After 2008, patents cite NIH-funded research 12% to 27% more often. Nonfunded research, funded research in journals unaffected by the mandate, and academic citations see no change. These estimates are consistent with a model of search for useful knowledge. Inefficiency caused by academic publishing may be substantial.

Abstract We study the first-order asymptotic properties of a class of estimators of the structural parameters in dynamic discrete choice games. We consider K-stage policy iteration (PI) estimators, where K denotes the number of PIs employed in the estimation. This class nests several estimators proposed in the literature. By considering a “pseudo likelihood” criterion function, our estimator becomes the K-pseudo maximum likelihood (PML) estimator in Aguirregabiria and Mira (2002, 2007). By considering a “minimum distance” criterion function, it defines a new K-minimum distance (MD) estimator, which is an iterative version of the estimators in Pesendorfer and Schmidt-Dengler (2008) and Pakes et al. (2007). First, we establish that the K-PML estimator is consistent and asymptotically normal for any $K \in N$. This complements findings in Aguirregabiria and Mira (2007), who focus on K=1 and K large enough to induce convergence of the estimator. Furthermore, we show under certain conditions that the asymptotic variance of the K-PML estimator can exhibit arbitrary patterns as a function of K. Second, we establish that the K-MD estimator is consistent and asymptotically normal for any $K \in N$. For a specific weight matrix, the K-MD estimator has the same asymptotic distribution as the K-PML estimator. Our main result provides an optimal sequence of weight matrices for the K-MD estimator and shows that the optimally weighted K-MD estimator has an asymptotic distribution that is invariant to K. The invariance result is especially unexpected given the findings in Aguirregabiria and Mira (2007) for K-PML estimators. Our main result implies two new corollaries about the optimal 1-MD estimator (derived by Pesendorfer and Schmidt-Dengler (2008)). First, the optimal 1-MD estimator is efficient in the class of K-MD estimators for all $K \in N$. In other words, additional PIs do not provide first-order efficiency gains relative to the optimal 1-MD estimator. Second, the optimal 1-MD estimator is more or equally efficient than any K-PML estimator for all $K \in N$. Finally, the Appendix provides appropriate conditions under which the optimal 1-MD estimator is efficient among regular estimators.

Kirk, Reppenhagen, and Tucker (2014) find that investors use individual analyst forecasts as additional earnings benchmarks. We investigate whether executives manage earnings to beat these individual benchmarks. Using year-end effective tax rate (ETR) manipulation as our setting, we find that firms decrease ETRs from 3rd to 4th quarter to meet or beat a greater percentage of individual forecasts. We also find some evidence that firms use incremental ETR changes to meet forecasts by key analysts. After controlling for the distance to the nearest forecast, our evidence shows that firms are more likely to beat an incremental forecast with a decrease in ETR compared to missing an incremental forecast with an increase in ETR. Our study highlights the strategic nature of earnings management by providing evidence that managers consider individual forecasts to calibrate earnings management decisions.

This study investigates whether brokerage houses appear to provide stock tips to politicians. Our results indicate that trades by politicians who are politically connected to the brokerage house where the trade is executed are more profitable. Our estimates suggest that these connected trades earn an incremental 0.3% over a five-day window relative to the politician's average profitability. Given the average number of trades our sample politicians execute in a year, the 0.3% return per trade translates to an incremental $3,411 in trading profits each year. We provide additional support by investigating the frequency and differential profitability of politicians' trades immediately before the brokerage house issues a revised recommendation, as well as during a period when Goldman, Sachs & Co. was sanctioned for providing stock tips to high priority clients. Additional tests suggest that brokerages may provide stock tips to politicians in exchange for favorable legislative outcomes or political information.

Abstract Should policy communications aim at anchoring expectations of the policy instrument (“keep interest rates at zero until date τ”) or of the targeted outcome (“do whatever it takes to bring unemployment down to y%”)? We study how the optimal approach depends on a departure from rational expectations. People have limited depth of knowledge and rationality, or form otherwise distorted beliefs about the behavior of others and the general equilibrium (GE) effects of policy. The bite of this distortion on implementability and welfare is minimized by target-based guidance if and only if GE feedback is strong enough. This offers a rationale for why central banks should shine the spotlight on unemployment when faced with a prolonged liquidity trap, a steep Keynesian cross, or a large financial accelerator.

We use linked birth and education records from Florida to investigate how the identification of childhood disabilities varies by race and school racial composition. Using a series of decompositions, we find that black and Hispanic students are identified with disabilities at lower rates than are observationally similar white students. Black and Hispanic students are overidentified in schools with relatively small shares of minorities and substantially underidentified in schools with large minority shares. Our results are consistent with a heightened awareness among school officials of disabilities in students who are racially and ethnically distinct from the majority race in the school.

ABSTRACT This study investigates how sophisticated market participants use tax‐based information by examining whether analysts' street effective tax rates (ETRs) are informative. When assessing firm performance, analysts exclude items they believe do not reflect current performance, resulting in “street” metrics such as street ETR. However, evidence on the properties of the components of street earnings is limited. Examining the informativeness of street ETRs is important because taxes are a significant component of earnings, and the extent to which analysts understand taxes and incorporate them into their analyses is not clear. Using a hand‐collected sample of analyst reports, we find that while approximately 35% of street ETRs have at least one tax‐specific exclusion, over 90% reflect the tax effects of pre‐tax exclusions. Further, both tax‐specific exclusions and the tax effects of pre‐tax exclusions significantly contribute to differences between GAAP and street ETRs. Consistent with analysts' understanding of the implications of tax and nontax exclusions, our results suggest that street tax metrics exhibit greater predictive ability about future tax outcomes and provide more information to investors than GAAP tax metrics. We also find that ETR exclusions are of higher quality when the magnitude of the potentially excluded item is greater and when managers disclose pro forma earnings. Collectively, our findings suggest that analysts understand taxes, but selectively exert effort to incorporate tax‐based information into their assessment of firm performance. Our study should be informative to regulators and users of financial information because it provides evidence regarding the usefulness of street earnings metrics.

ABSTRACT Economic downturns create uncertainty about a firm's operations and make it disproportionately harder for outside market participants to assess the firm's prospects. We posit that in this environment, management earnings forecasts will be more informative to investors and analysts. Consistent with this prediction, we find larger stock price reactions and analyst forecast revisions to news in management forecasts during downturns. Holding the amount of news in forecasts constant, stock price reactions to management forecasts are also greater than those to analyst forecasts. We also find that relative to analyst forecasts, management forecast accuracy increases during downturns, suggesting that investors justifiably assess management forecasts as more informative. Overall, we document that macroeconomic conditions create time‐series variation in the informativeness of different sources of information to outside market participants.