Research

This paper provides the first causal evidence that entrepreneurial activity diffuses through immediate neighborhood ties. I exploit residential moves in North Carolina to study whether the arrival of an entrepreneurial next-door neighbor increases business formation among incumbent residents. Merging statewide business registrations, voter files, and property transaction data, I construct a panel linking individuals to their closest neighbors and entrepreneurial outcomes over nearly two decades. Using a nearest-neighbor design with highly granular fixed effects, I find that exposure to an entrepreneurial neighbor raises the probability of business entry by 4–9 percent within five years. Effects are concentrated among immediate neighbors, attenuate sharply with distance, and are driven by arrivals who actually reside nearby. Most entry occurs in unincorporated, lower-cost businesses, while exposure to high-quality entrepreneurs increases the likelihood of starting incorporated firms. These findings show that face-to-face residential interactions are a powerful and highly localized channel through which entrepreneurship spreads.

Has the financialization of single-family housing shifted the age at which households enter homeownership? I study this question using deed records linked to voter-file age data, covering more than one million individual home purchases. I measure local financialization using the tract-level penetration of institutional long-term rental owners and distinguish first-time buyers from repeat buyers using the universe of prior individual deeds. Descriptively, institutional penetration is not associated with a large decline in the share of first-time buyers, but it is associated with changes in the composition of repeat purchasers and with purchases of institutional-style starter homes. To address endogenous investor location choice, I construct a shift-share instrument that interacts 2000 tract housing suitability for institutional rental operation with the national rise of online property-management technology and leave-one-out property-management market size (following Gorback, Qian, and Zhu, 2025). The instrument strongly predicts institutional rental growth in the cross-section and delivers quasi-experimental variation in local financialization. Preliminary purchase-level IV estimates suggest that a one-standard-deviation increase in institutional rental ownership raises the age of first-time buyers by roughly 0.7–1 year, while leaving the probability that a purchase is by a first-time buyer and the age of repeat buyers largely unchanged. These results suggest that financialization may not primarily exclude first-time buyers from ownership, but instead delays when marginal households enter the housing wealth ladder. In that sense, institutional ownership can reshape life-cycle wealth accumulation not by eliminating homeownership, but by postponing the start of leveraged housing equity formation.

Why do some policy issues become partisan flashpoints while other, equally consequential problems remain politically quiet? This paper develops a theory and measurement framework for the political selection of public attention. We argue that uncertainty creates room for competing narratives, but that uncertain issues become politicized only when their consequences can be mapped onto partisan or group cleavages and when emphasizing them is electorally useful. We combine large-scale newspaper text, C-SPAN political speech, public-opinion data, and measures of group-level policy exposure to construct topic-by-time measures of pre-politicization uncertainty, wedge potential, electoral fit, realized politicization, and media attention. The empirical analysis tests whether the interaction of these forces predicts which policy topics politicians transform into partisan conflict and whether politicized speech subsequently redirects scarce news attention across issues. By separating attention from politicization, the paper opens the black box of political divisiveness and offers a framework for studying how electoral competition may distort the public agenda, directing attention toward issues that are narratively exploitable rather than those with the greatest social stakes.

A three-factor no-arbitrage stochastic commodity pricing model is calibrated to copper using analysts' predictions provided by Bloomberg's Commodity Price Forecast and futures prices from the COMEX and LME metals exchanges. The model generates futures prices, expected spot prices and time-varying risk premiums for different maturities. Results show that between October 2010 and June 2018 both exchanges exhibit a positive average risk premium for each maturity. The risk premiums for both exchanges are also shown to be stochastic, with short maturities having higher average values and greater volatility. In addition, the futures prices of COMEX values were greater than those LME with a mean difference of 0.477% and the LME exhibits higher averages values than COMEX for expected spot prices and risk premiums, with differences of 0.438% and 0.354%, respectively. As for risk premium volatility, the estimate for COMEX is 0.993% greater than that for LME. Statistically significant evidence is also given for the cointegration of the two markets. An empirical analysis shows that the main determinants of the variation in copper risk premiums are variations in COMEX inventories, hedging pressure, the default premium, the Chicago Board Options Exchange Volatility Index and the return on the NASDAQ Emerging Market Index. Finally, the approach is used for estimating expected copper spot prices, thus making it a useful tool for practitioners and policy makers who use expected copper prices as the basis for their investment and risk-management decisions.

@article{cifuentes2020expected,
  title={Expected prices, futures prices and time-varying risk premiums: The case of copper},
  author={Cifuentes, Sebasti{\'a}n and Cortazar, Gonzalo and Ortega, Hector and Schwartz, Eduardo S},
  journal={Resources Policy},
  volume={69},
  pages={101825},
  year={2020},
  publisher={Elsevier}
}