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Working Papers

Happiness, Contentment and Other Emotions for Central Banks

Abstract

We show that data on satisfaction with life from over 600,000 Europeans are negatively correlated with the unemployment rate and the inflation rate. Our preferred interpretation is that this shows that emotions are affected by macroeconomic fluctuations. Contentment is, at a minimum, one of the important emotions that central banks should focus on. More ambitiously, contentment might be considered one of the components of utility. The results may help central banks understand the tradeoffs that the public is willing to accept in terms of unemployment for inflation, at least in terms of keeping the average level of one particular emotion (contentment) constant. An alternative use of these data is to study the particular channels through which macroeconomics affects emotions. Finally, work in economics on the design of monetary policy makes several assumptions (e.g., a representative agent, a summary measure of emotions akin to utility exists and that individuals only care about income and leisure) that can be used to interpret our results as weights in a social loss function.

Purchase the paper from SSRN.com ($5): http://papers.nber.org/papers/w13622

New Framework for Measuring and Managing Macrofinancial Risk and Financial Stability

Abstract

This paper proposes a new approach to improve the way central banks can analyze and manage the financial risks of a national economy. It is based on the modern theory and practice of contingent claims analysis (CCA), which is successfully used today at the level of individual banks by managers, investors, and regulators. The basic analytical tool is the risk-adjusted balance sheet, which shows the sensitivity of the enterprise's assets and liabilities to external "shocks." At the national level, the sectors of an economy are viewed as interconnected portfolios of assets, liabilities, and guarantees—some explicit and others implicit. Traditional approaches have difficulty analyzing how risks can accumulate gradually and then suddenly erupt in a full-blown crisis. The CCA approach is well-suited to capturing such "non-linearities" and to quantifying the effects of asset-liability mismatches within and across institutions. Risk-adjusted CCA balance sheets facilitate simulations and stress testing to evaluate the potential impact of policies to manage systemic risk.

Purchase the paper from SSRN.com ($5): http://papers.nber.org/papers/w13607

Does Individual Performance Affect Entrepreneurial Mobility? Empirical Evidence from the Financial Analysis Market

Abstract

Our paper contributes to the studies on the relationship between workers' human capital and their decision to become self-employed as well as their probability to survive as entrepreneurs. Analysis from a panel data set of research analysts in investment banks over 1988-1996 reveals that star analysts are more likely than non-star analysts to become entrepreneurs. Furthermore, we find that ventures started by star analysts have a higher probability of survival than ventures established by non-star analysts. Extending traditional theories of entrepreneurship and labor mobility, our results also suggest that drivers of turnover vary by destination: (a) turnover to entrepreneurship and (b) other turnover. In contrast to turnover to entrepreneurship, star analysts are less likely to move to other firms than non-star analysts.

Purchase the paper from SSRN.com ($5): http://papers.nber.org/papers/w13633

The Impact of Component Modularity on Design Evolution: Evidence from the Software Industry

Abstract

Much academic work asserts a relationship between the design of a complex system and the manner in which this system evolves over time. In particular, designs which are modular in nature are argued to be more "evolvable," in that these designs facilitate making future adaptations, the nature of which do not have to be specified in advance. In essence, modularity creates "option value" with respect to new and improved designs, which is particularly important when a system must meet uncertain future demands. Despite the conceptual appeal of this research, empirical work exploring the relationship between modularity and evolution has had limited success. Three major challenges persist: first, it is difficult to measure modularity in a robust and repeatable fashion; second, modularity is a property of individual components, not systems as a whole, hence we must examine these dynamics at the microstructure level; and third, evolution is a temporal phenomenon, in that the conditions at time t affect the nature of the design at time t+1, hence exploring this phenomenon requires longitudinal data. In this paper, we tackle these challenges by analyzing the evolution of a successful commercial software product over its entire lifetime, comprising six major "releases." In particular, we develop measures of modularity at the component level, and use these to predict patterns of evolution between successive versions of the design. We find that modularity has a strong and unambiguous impact on design evolution. Specifically, we show that i) tightly-coupled components are "harder to kill," in that they have a greater likelihood of survival in subsequent versions of a design; ii) tightly-coupled components are "harder to maintain," in that they experience more surprise changes to their dependency relationships that are not associated with new functionality; and iii) tightly-coupled components are "harder to augment," in that the mix of new components added in each version is significantly more modular than the legacy design.

Download the paper: http://www.hbs.edu/research/pdf/08-038.pdf