Harvard Business School

How can sophisticated negotiation bring about a more peaceful and prosperous Middle East? While a “grand bargain” to accomplish this lofty goal may seem implausible, the potential value of such an agreement would be vast for most Israelis, Palestinians, and key regional players—as well as for many global states. Yet the failure to successfully negotiate it would entail correspondingly huge potential costs for these parties. When the benefits of a deal are high and the costs of no deal are extreme, the underlying basis for a successful negotiation exists—that is, we can envision a collectively beneficial “zone of possible agreement” (ZOPA). The first task of this article is relatively easy: to describe the elements of such a grand bargain—an “Arab-Israeli-Palestinian Peace Initiative (AIPPI),” which should be announced by Saudi Arabia and/or the United Arab Emirates (UAE). The AIPPI would contain a vision of a permanent solution to the Israeli-Palestinian conflict in the form of a non-militarized Palestinian state with Israel enjoying normalized relations with moderate Sunni Arab regimes. As a point of departure for negotiating, it would detail the benefits to and obligations of Israelis, Palestinians, and Arab states required to realize this vision, encourage the creation of performance-based milestones toward this end, to be followed by an international conference. The analysis of this article then shows that a ZOPA likely exists among critical stakeholders despite formidable would-be blockers. Yet bringing about the AIPPI requires answering two much harder questions: What are the barriers to realizing it and what is a plausible path to overcome these barriers? Sketching credible answers to these two knotty questions is the main intended contribution of this article.

We study the real effects of market segmentation due to credit ratings using a matched sample of firms just above and just below the investment-grade cutoff. These firms have similar observables, including average investment rates. However, flows into high-yield mutual funds have an economically significant effect on the issuance and investment of the speculative-grade firms relative to their matches, especially for firms likely to be financially constrained. The effect is associated with the discrete change in label from investment-grade to speculative-grade, not with changes in continuous measures of credit quality. We do not find similar effects at other rating boundaries.

Consumers suffer significant losses from not acting on available information. These losses stem from frictions such as search costs, switching costs, and rational inattention, as well as what we call mental gaps resulting from wrong priors/worldviews, or relevant features of a problem not being top of mind. Most research studying such losses does not empirically distinguish between these mechanisms. Instead, we show that most highly cited papers in this area presume one mechanism underlies consumer choices and assume away other potential explanations, or collapse many mechanisms together. We discuss the empirical difficulties that arise in distinguishing between different mechanisms, and some promising approaches for making progress in doing so. We also assess when it is more or less important for researchers to distinguish between these mechanisms. Approaches that seek to identify true value from demand, without specifying mechanisms behind this wedge, are most useful when researchers are interested in evaluating allocation policies that strongly steer consumers towards better options with regulation, traditional policy instruments, and defaults. On the other hand, understanding the precise mechanisms underlying consumer losses is essential to predicting the impact of mechanism policies aimed primarily at reducing specific frictions or mental gaps without otherwise steering consumers. We make the case that papers engaging with these questions empirically should be clear about whether their analyses distinguish between mechanisms behind poorly informed choices, and what that implies for the questions they can answer. We present examples from several empirical contexts to highlight these distinctions.

We examine the optimal weighting of four tilts in U.S. equity markets from 1968 through 2014. We define a “tilt” as a characteristic-based portfolio strategy that requires relatively low annual turnover. This is a continuum, with small size (a very persistent characteristic) at one end of the spectrum and high frequency reversal at the other. Unlike low-turnover tilts, a full history of transaction costs is essential for determining the expected return of, and hence the optimal allocation to, less persistent, more turnover-intensive characteristics. The mean-variance optimal tilts toward value, size, and profitability are roughly equal to each other and equal to the optimal low-beta tilt. Notably, the low-beta tilt is not subsumed by the other three.

This is the first study to consider the relationship between open source software (OSS) and entrepreneurship around the globe. This study measures whether country-level participation on the GitHub OSS platform affects the founding of innovative ventures, and where it does so, for what types of ventures. We estimate these effects using cross-country variation in new venture founding and OSS participation. We propose an approach using instrumental variables, and cannot reject a causal interpretation. The study finds that an increase in GitHub participation in a given country generates an increase in the number of new technology ventures within that country in the subsequent year. The evidence suggests this relationship is complementary to a country’s endowments, and does not substitute for them. In addition to this positive change in the rate of entrepreneurship, we also find a change in direction—OSS contributions lead to new ventures that are more mission- and global-oriented and are of a higher quality. Together, the results suggest that OSS can boost entrepreneurial activity, albeit with a human capital prerequisite. Finally, we consider the implications for policies that encourage OSS as a lever for stimulating entrepreneurial growth.

We develop a model in which specialized bond investors must absorb shocks to the supply and demand for long-term bonds in two currencies. Since long-term bonds and foreign exchange are both exposed to unexpected movements in short-term interest rates, a shift in the supply of long-term bonds in one currency influences the foreign exchange rate between the two currencies, as well as bond term premia in both currencies. Our model matches several important empirical patterns, including the comovement between exchange rates and term premia, and the finding that central banks’ quantitative easing policies affect exchange rates. An extension of our model links spot exchange rates to the persistent deviations from covered interest rate parity that have emerged since 2008.

When do conversations lead people to generate better ideas? We conducted a field experiment at a startup boot camp to evaluate the impact of informal conversations on the quality of product ideas generated by participants. Specifically, we examine how the personality of an innovator (openness to experience, capturing creativity) and the personalities of her randomly assigned conversational peers (extroversion, measuring willingness to share information) affects the innovator's ideas. We find that open innovators who spoke with extroverted peers generated significantly better ideas than others at the boot camp. However, closed individuals produced mediocre ideas regardless of the individuals they interviewed, suggesting limited benefits of conversations for these people. More surprisingly, open individuals, who are believed to be inherently creative, produced worse ideas after they spoke with introverted peers, suggesting individual creativity's dependence on external information. Our study demonstrates the importance of considering the traits of both innovators and their conversational peers in predicting who will generate the best ideas.

Recent scholarship argues that experimentation should be the organizing principle for entrepreneurial strategy. Experimentation leads to organizational learning, which drives improvements in firm performance. We investigate this proposition by exploiting the time-varying adoption of A/B testing technology, which has drastically reduced the cost of testing business ideas. Our results provide the first evidence on how digital experimentation affects a large sample of high-technology start-ups using data that tracks their growth, technology use, and products. We find that, although relatively few firms adopt A/B testing, among those that do, performance improves by 30%–100% after a year of use. We then argue that this substantial effect and relatively low adoption rate arises because start-ups do not only test one-off incremental changes, but also use A/B testing as part of a broader strategy of experimentation. Qualitative insights and additional quantitative analyses show that experimentation improves organizational learning, which helps start-ups develop more new products, identify and scale promising ideas, and fail faster when they receive negative signals. These findings inform the literatures on entrepreneurial strategy, organizational learning, and data-driven decision making.

Contests that non‐contestants consume for entertainment are a fixture of economic, cultural and political life. We exploit injury‐induced changes to teams' line‐ups in a professional sports setting to examine whether individuals prefer to consume contests that have more uncertain outcomes. Studying data from the Australian Football League, we use an instrumental variables design to show that a one standard deviation increase in game outcome uncertainty causes, on average, an 11.2 per cent increase in attendance. When presented alongside ordinary least square's estimates, our results suggest that previous studies may heavily underestimate spectators' preferences for evenly balanced contests.

This study evaluates the impact of high-skilled immigrants on U.S. technology formation. We use reduced-form specifications that exploit large changes in the H-1B visa program. Higher H-1B admissions increase immigrant science and engineering (SE) employment and patenting by inventors with Indian and Chinese names in cities and firms dependent upon the program relative to their peers. Most specifications find limited effects for native SE employment or patenting. We are able to rule out displacement effects, and small crowding-in effects may exist. Total SE employment and invention increases with higher admissions primarily through direct contributions of immigrants.