1,721,160 research outputs found
Non-Bayesian updating: A theoretical framework
Full text linkThis paper models an agent in a multi-period setting who does not update according to Bayes' Rule, and who is self-aware and anticipates her updating behavior when formulating plans. Choice-theoretic axiomatic foundations are provided to capture updating biases that reflect excessive weight given to either prior beliefs, or alternatively, to observed data. A counterpart of the exchangeable Bayesian learning model is also described.Non-Bayesian updating, temptation and self-control, overreaction, underreaction, learning, law of small numbers
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Essays on Labor Markets in Developing Countries
Full text linkThis dissertation consists of three empirical essays on distortions in labor market outcomes in developing countries. Chapter 1 tests for downward nominal wage rigidity in markets for casual daily agricultural labor. It examines responses to rainfall shocks in 500 Indian districts from 1956-2008. First, nominal wages rise in response to positive shocks but do not fall during droughts. Second, after transitory positive shocks have dissipated, nominal wages do not fall back down. Third, inflation moderates these effects. Fourth, rigidities lower employment: landless laborers experience a 6% reduction in employment in the year after positive shocks. Fifth, consistent with separation failures, rationing leads to increased labor supply to small farms. New survey evidence suggests that agricultural workers and employers view nominal wage cuts as unfair and believe that they reduce effort. Chapter 2 (with Michael Kremer and Sendhil Mullainathan) describes the results of a field experiment that tests for self-control problems in labor supply. First, we find that workers will choose dominated contracts—which pay less for every output level but have a steeper slope—to motivate themselves. Second, effort increases significantly as workers’ (randomly assigned) payday gets closer. Third, the demand for dominated contracts (and their benefits) is concentrated amongst those with the highest payday effects. Finally, as workers gain experience, they appear to learn about their self control problems: the correlation between the payday effect and the demand for the dominated contract grows with experience. These results together suggest that self-control, in this context at least, meaningfully alters the firm’s contracting problem. Chapter 3 empirically examines the impact of multiple market failures on allocative efficiency in farm production in poor countries. In years when labor rationing is more likely in villages (due to wage rigidity), there is a 63% increase in sharecropped and leased land by small farmers. This is consistent with the prediction that distortions from a failure in one market can be reduced by reallocating other factors of production. In areas with worse credit access, there is less land adjustment in response to labor rationing. These results provide evidence for separation failures resulting from multiple missing markets
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Essays in Finance, Technology, and Behavior
No full textThis dissertation consists of three essays that study how patterns in human behavior inform models of finance and technology. The first essay develops methods to measure economic representations from language, and uses these representations to study how the market values firms. It finds that firms can be misvalued when they are misperceived, including during waves of investor attention to new technologies. The second essay, co-authored with Keyon Vafa, builds a framework to evaluate lookahead bias in pretrained language models, and finds evidence of the bias in applications to finance and political economy. It describes how to prevent lookahead bias by using time-indexed language models in forecasting analyses. The third essay, co-authored with Johnny Tang, analyzes how partisanship relates to economic beliefs, and finds partisan differences in optimism, attention to economic topics, and interpretation of economic shocks. It discusses how these differences in stated beliefs can help to interpret partisan differences in economic decisions.Economic
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Essays in Information Technology and Productivity
No full textThis dissertation studies the relationship between information technology and productivity in three domains. Chapter 1 examines a mobile software application that allows recipients of the Supplemental Nutrition Assistance Program (SNAP) to check their benefit balance. Recipients spend a large majority of benefits before halfway through a benefit deposit cycle. Using an event study, I show that the introduction of the application on average has small but significant impacts - around 5% - on the ability of recipients to extend the time frame over which they spend benefits within a cycle. These effects are higher for recipients who are new to SNAP, who are highest in the distribution of SNAP benefits, and who have the largest tendency pre-adoption to spend down quickly. The results are consistent with the impact of salience on consumer choice and offer evidence that such software tools may be a cost effective means to support policy goals.
Chapter 2 examines the impact of machine learning on public sector productivity in practice. Partnering with Yelp and the City of Boston, we run an experiment to compare an inspector-curated list of restaurants to inspect (i.e. business-as-usual) to a pair of algorithm-created lists based on empirical predictions of which restaurants are most likely to have health code violations. Our goal is to understand the gains from - and barriers to - implementing predictive algorithms to improve the city’s ongoing inspection operations. We present four main findings. First, even simple algorithms greatly outperform business-as-usual; the city can identify 50% more violations using the same number of inspections. Second, one key barrier to implementing an algorithm in managerial contexts is compliance. In our sample, inspectors were only half as likely to comply with a directive to inspect a restaurant based on the algorithm relative to restaurants based on their own judgment. Third, beyond efficiency differences, the algorithm also has equity implications. For example, relative to the inspector-created list, algorithms were more likely to target ethnic restaurants and major chains. Fourth, based on these results, Boston has proceeded with implementing a modified version of the algorithm into their ongoing inspection process.
Chapter 3 studies the theoretical impact of machine learning applied to the selection of public sector workers. Economists have become increasingly interested in studying the nature of production functions in social policy applications with the goal of improving productivity. Traditionally models have assumed workers are homogenous inputs. However, in practice, substantial variability in productivity means the marginal productivity of labor depends substantially on which new workers are hired--which requires not an estimate of a causal effect, but rather a prediction. We demonstrate that there can be large social welfare gains from using machine learning tools to predict worker productivity using data from two important applications - police hiring and teacher tenure decisions.Business Economic
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Essays on the Determinants of Human Capital
No full textThis dissertation consists of three empirical essays broadly concerned with the determinants of human capital. The first essay estimates the causal effect of exposure to maternal psychological stress generated by the 9/11 attacks on the cohort in utero that day. The analysis finds that cohorts exposed during the first or second trimester in New York City weighed less at birth and had shorter gestation lengths. Male and female newborns were affected similarly. At age six, boys were more likely to be in special education and more likely to be in kindergarten rather than first grade, with no effect on girls. Births outside New York City were not affected. The results suggest that psychological stress is an important channel through which adverse conditions experienced by pregnant women negatively impact the early life outcomes of in utero cohorts. The second essay (joint with Katherine Baldiga) presents experimental evidence of a gender difference in the valuation of job training as an explanation for the female advantage in human capital investment that has emerged in many high income countries. In an online labor market, we find that when subjects have limited experience with an unfamiliar task, women are more willing to pay for training than men, and women estimate that the returns to training are higher than men do. We find that task performance, the return to training, self-confidence, and risk aversion cannot explain the gender gap in valuing training. We present suggestive evidence that training may be valued by women for increasing their willingness to take on a challenge. The third essay tests the prediction of several biological theories that maternal condition impacts the sex ratio at birth and causes differential investment by child's sex with data from the Dominican Republic, a developing country with relatively neutral offspring sex preferences. The analysis finds that more educated women are more likely to give birth to sons, and women in the middle of the maternal age distribution are less likely to have a male child die during infancy. These results provide evidence that maternal condition is correlated with the sex composition of children.Economic
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Essays in Development Economics
No full textThis dissertation consists of four chapters, in two halves. The common, broad theme is the importance of time in problems which we often analyze statically.
In the first half, we consider the role of time in insurance. The gains from insurance arise from the transfer of income across states. Yet, by requiring that the premium be paid upfront, standard insurance products also transfer income across time. We consider the theoretical implications of this transfer across time in Chapter 2, and test them empirically in Chapter 1. We show that the intertemporal transfer can help explain low insurance demand, especially among the poor, and in a randomized control trial in Kenya we test a crop insurance product which removes it. The product is interlinked with a contract farming scheme: as with other inputs, the buyer of the crop offers the insurance and deducts the premium from farmer revenues at harvest time. The take-up rate is 72%, compared to 5% for the standard upfront contract, and take-up is highest among poorer farmers. Additional experiments and outcomes indicate that liquidity constraints, present bias, and counterparty risk are all important constraints on the demand for standard insurance.
In the second half, we consider the implications of time for policies on investments in durables. Such investment decisions are forward looking, so expectations over future policies matter. In Chapter 3 we argue public infrastructure often substitutes for, or complements, private durables. In such cases, private investment in durables depends on expectations over future public infrastructure. In turn, private investment affects future demand for, and hence investment in, public infrastructure. This creates a dynamic coordination game which can have multiple equilibria. If governments can commit early to future public infrastructure, they may do so. If they cannot, they may be driven to second best policies, such as early construction of public infrastructure. In Chapter 4 we consider Pigouvian taxation of durables. Dynamically and statically optimal Pigouvian subsidies on durables will differ in a growing economy. For durables with positive externalities, statically optimal subsidies will typically grow, whereas dynamically optimal policies may commit to eventually reducing subsidies.EconomicsDevelopment Economics; Insurance; Infrastructur
A memory based model of bounded rationality
No full textTitle from coverSeptember 2000. September 20, 2000--Abstrac
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Inductive Learning and Theory Testing: Applications in Finance
No full textThis thesis explores the opportunities for economic research that arise from importing empirical methods from the field of machine learning.
Chapter 1 applies inductive learning to cross-sectional asset pricing. Researchers have documented over three hundred variables that can explain differences in cross-sectional stock returns. But which ones contain independent information? Chapter 1 develops a framework, deep conditional portfolio sorts, that can be used to answer this question and that is based on ideas from the machine learning literature, tailored to an asset-pricing application. The method is applied to predicting future stock returns based on past stock returns at different horizons, and short-term returns (i.e. the past six months of returns) rather than medium- or long-term returns are recovered as the variables that convey almost all information about future returns.
Chapter 2 argues that machine learning techniques, although focusing on predictions, can be used to test theories. In most theory tests, researchers control for known theories. In contrast, chapter 2 develops a simple model that illustrates how machine learning can be used to conduct an inductive test that allows to control for some unknown theories, as long as they are covered in some way by the data. The method is applied to the theory that realization utility and nominal loss aversion lead to the disposition effect (the propensity to sell winners rather than losers). An inductive test finds that short-term price trends and other features of the price history are more important to predict selling decisions than returns relative to purchase price.
Chapter 3 provides another perspective on the disposition effect in the more traditional spirit of behavioral finance. It assesses the implications of different theories for an investor's probability to sell a stock as a function of the stock's return and then tests those implications empirically. Three different approaches that have been used in the literature are shown to lead to the, at first sight, contradictory findings that the probability to sell a stock is either V-shaped or inverted V-shaped in the stock's return. Since these approaches compute different conditional probabilities, they can be reconciled, however, when the conditioning set is taken into account.EconomicsMachine Learning; Behavioral Finance; Asset Pricin
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Three Essays on Local Economic Development in India
Full text linkThis dissertation examines the determinants of local economic and political development in India. In the first chapter, I study the impact that agricultural income shocks have on the local nonfarm economy. I find that positive rainfall shocks induce significant employment growth, not in the rural areas where agricultural production takes place but in the nearby towns. Manufacturing firms in particular respond to changes in agricultural production. Further investigation suggests that the most likely mechanism is a capital channel by which local agricultural surplus funds investments in urban manufacturing. In the second chapter, I examine the relationship between natural resource wealth and political outcomes. The interaction of mineral deposit locations and global price changes provide exogenous variation in the value of mineral wealth of state legislative assembly constituencies in India. I find that margins of victory, incumbency advantages and politician criminality are increasing in local mineral wealth. I test three channels for the criminality effect: (i) greater criminality in office; (ii) adverse selection of politicians into the political system; and (iii) greater success of criminal candidates in elections, finding the strongest evidence for the third effect. Finally, in the third chapter, I evaluate the importance of transportation costs to rural economic development. I take advantage of the allocation rules of a large-scale road construction program in India to estimate the impact of village roads on nonfarm economic activity. I find that new paved roads lead to large increases in village employment. Roads lead to an increase in firm size, suggesting that firms are inefficiently small when transport costs are high. Further, I find evidence that roads are most effective in the presence of electricity, suggesting complementarities between infrastructural investments.Economic
The Effect of Benefits Level on Take-up Rates: Evidence from a Natural Experiment
Full text linkThis paper exploits a quasi-natural experiment to study the effect of social benefits level on take-up rates. We find that households who are eligible for double benefits (twins) have much higher take-up rate - up to double - as compared to a control group of households. Our estimated effect of benefits level is much higher relative to the standard cross section estimates. This finding is less exposed to a selection bias that might plague much of the previous research on the link between benefits level and take-up. It provides strong empirical support for the level of benefits as a key factor in determining take-up rates.take-up, social benefits
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