The Federal Reserve Bank of Dallas covers the Eleventh Federal Reserve District, which includes Texas, northern Louisiana and southern New Mexico, a district sometimes referred to as the Oil Patch.The Federal Reserve Bank of Dallas is one of 12 regional Reserve Banks that, along with the Board of Governors in Washington, D.C., make up the nation's central bank. The Dallas Fed is the only one where all external branches reside in the same state (although the region itself includes northern Louisiana as well as southern New Mexico).The Dallas Fed has branch offices in El Paso, Houston, and San Antonio.The Dallas bank is located at 2200 Pearl St. in the Uptown neighborhood of Oak Lawn, just north of downtown Dallas and the Dallas Arts District.Prior to 1992, the bank was located at 400 S. Akard Street, in the Government District in Downtown Dallas. The older Dallas Fed building, which opened in 1921, was built in the Beaux-arts style, with large limestone structure with massive carved eagles and additional significant detailing; it is a City of Dallas Designated Landmark structure. The current Dallas Fed building, opened in September 1992, was designed by three architectural firms: Kohn Pedersen Fox Associates, New York; Sikes Jennings Kelly & Brewer, Houston; and John S. Chase, FAIA, Dallas and Houston, Dallas-based Austin Commercial Inc. served as project manager and general contractor.
We provide evidence that the quantitative importance of the Haar prior for posterior impulse response inference has been overstated. How sensitive posterior inference is to the Haar prior depends on the width of the identified set. This width depends not only on how much the identified set is narrowed by the identifying restrictions but also on the data through the reduced-form model parameters. Hence, the role of the Haar prior can be assessed only on a case-by-case basis. We show by example that when the identification is sufficiently tight, posterior inference based on a Gaussian-inverse Wishart-Haar prior is justified.
Using a transformation of the autoregressive distributed lag model due to Bewley, a novel pooled Bewley (PB) estimator of long-run coefficients for dynamic panels with heterogeneous short-run dynamics is proposed. The PB estimator is directly comparable to the widely used Pooled Mean Group (PMG) estimator, and is shown to be consistent and asymptotically normal. Monte Carlo simulations show good small sample performance of PB compared to the existing estimators in the literature, namely PMG, panel dynamic OLS (PDOLS), and panel fully-modified OLS (FMOLS). Application of two bias-correction methods and a bootstrapping of critical values to conduct inference robust to cross-sectional dependence of errors are also considered. The utility of the PB estimator is illustrated in an empirical application to the aggregate consumption function.
U.S. tariff policy has historically balanced competing goals—revenue, protection, and reciprocity. Policy priorities have shifted over time in response to changing economic and political conditions. Using a calibrated general equilibrium model, we illustrate these trade-offs through the lens of tariff Laffer curves. A 70 % tariff maximizes U.S. revenue only in the absence of retaliation; this optimum falls to 30 % with reciprocal tariffs. A unilateral 25 % tariff delivers the largest domestic consumption gains through favorable terms-of-trade effects, though these gains vanish under retaliation. Simulations also show that multilateral retaliatory tariffs can partially offset losses for Mexico and Canada—unless escalation triggers broader trade conflict. The 2018–19 tariff war further illustrates how targeted tariffs distort relative prices and cross-border resource allocation.
This paper introduces novel measures to assess the effectiveness of inflation targeting (IT) and examines its performance across a broad sample of advanced economies (AEs) and emerging market and developing economies (EMDEs). Utilizing synthetic control methods, the study reveals heterogeneous effects of IT on inflation. The results indicate modest reductions in inflation levels, with greater gains observed in EMDEs compared to AEs. Statistically significant reductions are found in approximately one-third of the countries. However, nearly half of the economies experienced substantial improvements in stabilizing inflation near target levels under IT, relative to estimated counterfactual scenarios. IT also enhances economic resilience cushioning inflation from large external shocks, particularly during the 2007-09 Global Financial Crisis, with statistically significant gains observed in two-thirds of EMDEs. Additionally, the effectiveness of IT-both in shifting inflation levels and maintaining stability around target-is significantly correlated with indices of exchange rate stability and monetary policy independence, especially in EMDEs. These
