Countries? ” If there exist aggregate production functions representing approximately the same technology across countries, then the vastly higher output per worker in richer countries implies that capital per worker must be much higher in these countries, and diminishing returns implies a much lower rate of return to capital in rich than in poor countries. The details of the calculation depend, of course, on specific assumptions. However, the magnitudes are sufficiently large that the absence of massive capital flows to the poorest countries is properly seen as a fundamental puzzle. Lucas considers the possibility that capital market imperfections permit the existence of a gap in the returns to capital across countries, but argues that this cannot account for most of the difference implied by his calculation. He, therefore, raises the possibility that there are huge differences in human capital across countries, and externalities associated with these differences imply that returns to physical capital are not so different across countries with even large differences in physical capital per worker. Accordingly, there is no mystery about the lack of physical capital flows. In contrast, Abhijit V. Banerjee and Esther C. Duflo (2005) review a good deal of evidence, mostly from India, showing widely varying and often very high real interest rates. In addition, ∗We are grateful to Marcus Noland for the initial conversation that led to this paper, to Erica Field, Barbara O’Brien and Yuichi Kitamura for valuable comments, and to Hyungi Woo, Tavneet Suri, and Patrick Amihere

Exploiting regression discontinuity designs in Brazilian, Indian, and Canadian first-past-the-post elections, we document that second-place candidates are substantially more likely than close third-place candidates to run in, and win, subsequent elections. Since both candidates lost the election and had similar electoral performance, this is the effect of being labeled the runner-up. Selection into candidacy is unlikely to explain the effect on winning subsequent elections, and we find no effect of finishing in third place versus fourth place. We develop a simple model of strategic coordination by voters that rationalizes the results and provides further predictions that are supported by the data.

We study a unique field experiment in India in which 1.5 million stock investors face lotteries for the random allocation of shares. We find that the winners of these randomly assigned initial public offering (IPO) lottery shares are significantly more likely to hold them than lottery losers 1, 6, and even 24 months after the random allocation. This finding strongly evokes laboratory findings of an “endowment effect” for risky gambles, and persists in samples of highly active investors, suggesting along with additional evidence that this behaviour is not driven by inertia alone. The effect decreases as experience in the IPO market increases, but remains even for very experienced investors. Leading theories of the endowment effect based on reference-dependent preferences are unable to fully explain these and other findings in the data.

We study a natural experiment in which 1.5 million investors participate in allocation lotteries for Indian IPO stocks. Investors who win the lottery and obtain IPO stocks that rise in value increase portfolio trading volume in non-IPO stocks relative to lottery losers; the effects are negative for lottery winners obtaining IPO stocks that fall in value. A model in which agents learn from random experience about their ability to operate in the market environment best explains the results. Investors who have received multiple past IPO allocations show smaller responses, suggesting that learning/selection moderates these responses to noise shocks.

We study a natural experiment in the Indian mutual funds sector that created a 22-month period in which closed-end funds were allowed to charge an arguably shrouded fee, whereas open-end funds were forced to charge entry loads. Forty-five new closed-end funds were started during this period, collecting $7.6 billion US, whereas only two closed-end funds were started in the 66 months prior to this period, collecting $42 billion US, and no closed-end funds were started in the 20 months after this period. We estimate that investors lost and fund firms gained approximately $350 million US due to this shrouding. JEL: D14, G23, G28, O16

We conduct a series of field experiments to evaluate the quality of advice provided by life insurance agents in India. Agents overwhelmingly recommend unsuitable, strictly dominated products that provide high commissions to the agent. Agents cater to the beliefs of uninformed consumers, even when those beliefs are wrong. We also find that agents appear to focus on maximizing the amount of premiums (and therefore their commissions) that customers pay, as opposed to focusing on how much insurance coverage customers need. A natural experiment requiring disclosure of commissions for a specific product results in agents recommending alternative products with high commissions but no disclosure requirement. A follow-up agent survey sheds light on the extent to which poor advice reflects both the commission incentives and agents’ limited product knowledge.