Conference Agenda

Banks differ in specialization. We study the aggregate and distributive effects of financial development in a heterogeneous-firm model where banks specialize in domestic or foreign activities. Internationally oriented banks promote the growth of larger incumbent exporters. Locally specialized banks enable financially vulnerable firms to enter foreign markets but induce incumbent exporters to focus on domestic markets, reducing their export intensities and fragmenting the export sector. The quantitative analysis reveals that financial development boosts total output, moderates inter-firm inequalities driven by internationalization, but may reduce aggregate trade. The predictions are supported by evidence from a major Italian banking deregulation.

We document a novel empirical pattern: Elevated foreign financial vulnerabilities shift the entire U.S. growth distribution leftward, not merely the downside tail, suggesting structural effects on potential output rather than purely cyclical impacts. This stands in sharp contrast to financial conditions, which primarily affect tail risk. Building on Adrian et al. (2019)’s Growth-at-Risk framework, we develop a Transmission Growth-at-Risk (TGaR) model that treats foreign financial conditions as shocks and foreign vulnerabilities as shock amplifiers. While the effects of financial conditions peak in the near term, foreign vulnerabilities weigh on U.S. GDP at a medium-term horizon, consistent with vulnerabilities being slow-moving state variables. Asset valuation pressures and financial sector leverage abroad are key amplifiers, operating through trade and dollar funding channels of similar magnitude. Out of sample, TGaR improves significantly predictive accuracy. During the European sovereign debt crisis from 2010 to 2012, elevated European vulnerabilities shifted the U.S. growth distribution leftward by about 1.5 percentage points despite stabilizing domestic conditions. In the Global Financial Crisis, U.S.-originated shocks were amplified by foreign vulnerabilities and returned to worsen domestic outcomes, illustrating “spillback” effects beyond standard one-way spillover models.

We examine whether the data revolution promotes acquisition activities at the firm level. We develop firm-year data assets measures using a combination of economic modeling and a large language model. Since 2010, data assets have expanded and increasingly concentrated in large firms. Firms with greater data assets are more likely to be a bidder, with the effect significantly stronger among large firms. Evidence supports a defensive “eat or be eaten” motive: data-driven M\&A activity is stronger in industries with a higher concentration of small- and medium-sized data-intensive firms and is often value-destroying. Data assets improve the information environment and reduce financing costs are also channels for data-asset-induced mergers. Our findings are robust to alternative proxies for data assets and remain consistent under instrumental variable estimations. The data era has intensified defensive and inorganic growth, accruing disproportionately to large firms.

The well-known Taylor rule creates a straightforward linear relationship between the interest rate, inflation, and output gap in the original version. Forward-looking assumption of the central bank’s behavior is a noteworthy expansion of this rule over the last years. Instead of current values of the variables, forward looking version of the rule uses predicted variables. In this paper, forward-looking Taylor rule is being estimated for the case of Turkey using the most updated quarterly data (2002Q1-2021Q3). The results of the estimations show that, the Central Bank of Turkey reacts to changes in the output gap and inflation rate when there is a concern for price stability and economic activity. According to the baseline model estimates, the CBRT has an anti-inflation bias, focusing more on inflation stabilization than output stabilization.