Knowledge that Transforms

This paper shows that the growing disparities between big and small cities in the U.S. since 1980 can be explained by firms endogenously responding to a skill-biased technology shock. With the introduction of a new skill-biased technology that is high fixed cost but low marginal cost, firms endogenously adopt more in big cities, cities that offer abundant amenities for high-skilled workers, and cities that are more productive in using high-skilled labour. In cities with more adoption, small and unproductive firms are more likely to exit the market, increasing the equilibrium rate of turnover or business dynamism—a selection effect similar to Melitz (2003). Differences in technology adoption and selection account for three key components of the growing regional disparities, known as the Great Divergence: (1) big cities saw a larger increase in the relative wages and supply of skilled workers, (2) big cities saw a smaller decline in business dynamism, and (3) firms in big cities invest more intensively in information and communication technology.

We exploit information in patent applications to construct an instrumental variable for the identification of technology news shocks that relaxes all the identifying assumptions traditionally used in the literature. The instrument recovers news shocks that have no effect on aggregate productivity in the short-run, but are a significant driver of its trend component. The shock prompts a broad-based expansion in anticipation of the future increase in total factor productivity (TFP), with output, consumption, and investment all rising well before any material increase in TFP is recorded. Despite the positive conditional comovements, the shock only accounts for a modest share of fluctuations of macroeconomic aggregates at business cycle frequencies. Financial markets price-in news shocks on impact, while most of the macro aggregates respond with some delay.

This paper studies the effects of the court-ordered removal of children from home on health, crime, and education. To isolate causal effects, I exploit quasi-random variation in judge assignment together with across-judge variation in the tendency to favour removal in an instrumental variable design. Using a novel data set (N=26,579) based on Swedish court documents that I transcribe and link with detailed register data, I find that court-ordered out-of-home placement has large adverse effects on the mortality of the marginal child. These effects are primarily driven by suicides that occur while the removed child is still placed in out-of-home care. Removal also causes an increase in hospitalizations for mental illness and non-narcotic crimes. There is little evidence of adverse health effects for birth parents. I explore potential explanations for the detrimental effects on child health. Adverse care conditions and peer exposure appear to be important channels.

I quantitatively analyse the macroeconomic impacts of raising capital requirements in a model in which heterogeneous firms may choose either intermediated or direct finance. Heterogeneous banks compete with other banks and the bond market, fund loans with insured deposits and costly equity (subject to a minimum capital-to-asset ratio), and monitor borrowers. I find that tighter capital requirements reduce costly bank failures while having only small effects on key macroeconomic aggregates, and that raising capital requirements above current levels can be welfare-improving. Three main forces give rise to these results. First, even though banks cut loan supply for a given level of net worth under a tighter capital requirement, in equilibrium banks’ net worth rises to dampen this effect. Second, intense competition from the non-bank sector disciplines banks’ lending responses to tighter regulation. Third, substitution by corporate firms offsets much of the decline in debt financing associated with tighter bank loan supply. As a corollary, almost all of the modest costs associated with tighter capital requirements are concentrated within the bank-dependent non-corporate sector.

What characteristics of news generate over-or-underreaction? We study the asset-pricing consequences of diagnostic expectations, a model of belief formation based on the representativeness heuristic, in a setting where news events are drawn from categories with extreme distributions of fundamentals. Our model predicts greater overreaction to news belonging to categories with more extreme outliers, or tail events. We test our theory on a comprehensive database of corporate news that includes news from twenty-four different categories, including earnings announcements, product launches, mergers and acquisition, business expansions, and client-related news. We find theory-consistent heterogeneity in investor reaction to news, with more overreaction in the form of greater post-announcement return reversals and trading volume for news categories with more extreme distributions of fundamentals.

This article studies the efficient allocation in an economy in which firms are connected through input–output linkages and must pay a fixed cost to produce. When economic conditions are poor, some firms might decide not to operate, thereby severing the links with their neighbours and changing the structure of the production network. Since producers benefit from having access to additional suppliers, nearby firms tend to operate, or not, together. As a result, the production network features clusters of operating firms, and the exit of a producer can create a cascade of firm shutdowns. While well-connected firms are better able to withstand shocks, they trigger larger cascades upon exit. The theory also predicts how the structure of the production network changes over the business cycle. As in the data, recessions are associated with more dispersed networks that feature fewer highly connected firms. In the calibrated economy, the endogenous reorganization of the network substantially dampens the impact of idiosyncratic shocks on aggregate fluctuations.

A key question in labour market research is how the unemployment insurance system affects unemployment rates and labour market dynamics. We provide new answers to this old question by studying one of the largest unemployment insurance reforms in recent decades, the German Hartz reforms. On average, lower separation rates into unemployment account for 76% of declining unemployment after the reform, a fact unexplained by existing research focussing on job-finding rates. Exploiting institutional changes by age, employment duration, and wages, we establish a causal link between the reform and changes in labour market dynamics. Relying on the labour market theory, we generalize our empirical findings beyond the German case and establish separation rate changes as an important macroeconomic adjustment channel after unemployment insurance reforms. We derive analytically that the change of separation rates increases in proportion to average unemployment duration suggesting an equally important role for most other European labour markets.

Using a dynamic panel approach, we provide empirical evidence that negative health shocks significantly reduce earnings. The effect is primarily driven by the participation margin and is concentrated among the less educated and those in poor health. Next, we develop a life-cycle model of labour supply featuring risky and heterogeneous frailty profiles that affect individuals’ productivity, likelihood of access to social insurance, disutility from work, mortality, and medical expenses. Individuals can either work or not work and apply for social security disability insurance (SSDI/SSI). Eliminating health inequality in our model reduces the variance of log lifetime (accumulated) earnings by 28% at age 55. About 60% of this effect is due to the impact of poor health on the probability of obtaining SSDI/SSI benefits. Despite this, we show that eliminating the SSDI/SSI program reduces ex ante welfare.

How do movements in the distributions of bank size and income affect the macroeconomy? To answer this question, we develop a dynamic general equilibrium model with heterogeneous financial intermediaries, incomplete markets, and aggregate uncertainty. We find that market incompleteness and uninsured idiosyncratic bank rate of return risk generate minimal concentration in the bank net worth distribution, leading to an “as-if” result, whereby the economy behaves as if it had a representative bank. However, introducing ex ante heterogeneity in the banks’ rates of return significantly raises concentration and amplifies real and financial fluctuations relative to the representative-bank case, as this increases a key sufficient statistic, the average marginal propensity to lend. We then extend the model with two empirically validated features of the banking sector—countercyclical return risk and deposit market power—and show that these amplify and dampen aggregate fluctuations, respectively. Finally, because in the model with ex ante heterogeneity the distribution of bank size is highly concentrated, shocks to the largest banks can account for almost all of the aggregate variation that is due to idiosyncratic risk, leading to granular banking and economic cycles. The failure of granular banks (“too big to fail”) produces sizeable macroeconomic crises.

We develop a satisficing model of choice in which the available alternatives differ in their inherent complexity. We assume—and experimentally validate—that complexity leads to errors in the perception of alternatives’ values. The model yields sharp predictions about the effect of complexity on choice probabilities, some of which qualitatively contrast with those of maximization-based choice models. We confirm the predictions of the satisficing model—and thus reject maximization—in a novel data set with information on hundreds of millions of real-world chess moves by highly experienced players. Looking beyond chess, our work offers a blueprint for incorporating complexity at the level of individual objects into models of choice and for detecting satisficing outside of the laboratory.