Alan M. Taylor | Macro Paper Warehouse

Globalization and Capital Markets

Written as the financial-globalization backlash of the late 1990s was at its height, this chapter asks whether the integration of world capital markets at the turn of the twenty-first century was unprecedented, and what governed its rise and fall. The received narrative is a U – high mobility under the classical gold standard, destruction between 1914 and 1945, slow reconstruction under Bretton Woods, and a renewed rise after the early 1970s – and the authors are explicit that this is a hypothesis to be tested rather than a result, labelling their own stylised figure of it “Conjecture?” with the source listed as “Introspection.” The explanation they propose is the open-economy policy trilemma: since a government can have at most two of free capital movement, a fixed exchange rate, and a monetary policy oriented to domestic goals, capital mobility survived wherever politics supported one of the corner solutions and was suppressed wherever governments tried to occupy the middle ground. Because no single measure of market integration is decisive – price convergence and flow volumes both fail as criteria, and “all such tests may be able to evaluate market integration, but only as a joint hypothesis test where some auxiliary assumptions are needed” – the paper runs a battery. On quantities, foreign assets were about 7 percent of world GDP in 1870, just under 20 percent at the 1900-14 zenith of the gold standard, 8 percent in 1930, 11 percent in 1938, 5 percent in 1945, 6 percent in 1960, 25 percent in 1980 and 62 percent in 1995 – so “the 1900-14 ratio of foreign investment to output in the world economy was not equaled again until 1980, but has now been approximately doubled,” with liabilities tracing the same path (21 percent in 1914, 11 percent in 1938, 2 percent in 1960, 30 percent in 1980, 79 percent in 1995). Measured against the GDP only of countries with data, however, the seven great creditors exceeded 50 percent from 1870 to 1914, a level “we only surpassed … as recently as 1990, and only narrowly even then.” On prices, long-term real interest differentials against the United States for Britain, France and Germany are stationary over the whole 1890-2000 span and in most subperiods, with the unit-root null rejected at 1 percent almost everywhere except the recent float; covered and quasi-covered nominal differentials since 1870 widen in exactly the periods the U predicts, and threshold estimates of the no-arbitrage band – roughly 19 basis points for New York-London and 35 for London-Berlin before 1914, against 60 and 91 in the interwar years and about 6 in the mid-1980s – put pre-1914 integration “truly impressive compared to conditions over the following half-century or more.” Cross-country dispersion of dollar equity returns follows the same U for the G7. The authors then argue that only policy can account for the mid-century collapse, since “technology is a poor candidate” – financial techniques were not forgotten in the 1930s, and some, such as foreign exchange futures, matured then. The political-economy section supplies supporting evidence from bond spreads: on a consistent 1870-1940 London panel, being on gold lowered spreads by about 57 basis points before 1914 and only peripheral countries were punished for public debt (7.2 basis points per 10 percentage points of debt to GDP), whereas for 1925-30 the gold dummy is insignificant or wrongly signed, core and periphery are no longer distinguished, debt sensitivity is roughly five times larger, and estimated reputational persistence falls from 0.68 to 0.30. Finally the paper insists on one large difference between the two globalizations. Pre-1914 flows were long-term and nearly one-way, so gross and net positions nearly coincided; today the same rich countries top both the asset and liability rankings, net positions have stayed very low since 1980, and the developing-country share of global liabilities has fallen from 33 percent in 1900 to 11 percent in the 1990s. Today’s integration is therefore “mostly a rich-rich affair, a process of ‘diversification finance’ rather than ‘development finance’,” and the Lucas paradox of capital failing to reach capital-poor countries is, if anything, sharper now than a century ago.

Local Projections

This 2025 Journal of Economic Literature survey by Òscar Jordà (who introduced the method in a 2005 AER paper) and Alan M. Taylor takes stock of local projections (LP) as a general framework for estimating impulse responses, arguing that LPs “help bridge the divide between current best practices in applied microeconomics and standard time series methods in macroeconomics.” The baseline LP estimates the impulse response at horizon h directly as the coefficient beta_h in a single OLS regression of y_{t+h} on the intervention s_t and lagged controls x_t, requiring one separate regression per horizon rather than iterating forward a fitted VAR; the authors identify four practical advantages over VARs – no cross-equation system constraints, straightforward accommodation of nonlinearities and heterogeneity, direct estimation of cumulative multipliers, and a natural extension to panel and difference-in-differences settings – while showing LP remains asymptotically equivalent to VAR-implied impulse responses (and to VAR-based Cholesky and long-run identification) whenever the underlying process truly is a VAR of the assumed order (citing Plagborg-Møller and Wolf 2021), and retains identification via LP-IV even in “non-invertible” settings where VAR identification from the reduced-form covariance matrix breaks down. The survey then works through the full LP toolkit: levels versus long-difference specifications (long-differencing “considerably reduces” the O(T^-1) small-sample bias that is severe for persistent, near-unit-root outcomes in short samples); horizon-by-horizon smoothing via B-splines or a Gaussian basis function; inference via Newey-West HAC standard errors, lag-augmented LP (which restores ordinary White standard errors with, per Montiel Olea and Plagborg-Møller 2021, correct uniform coverage across stationary, near-unit-root, and unit-root processes), system GMM for joint hypothesis tests across horizons, sup-t simultaneous confidence bands, and Lagrange-multiplier significance bands constructed under the null; identification via selection on observables, inverse-propensity weighting, long-run restrictions, and LP-IV; projection minimum distance (PMD) for recovering structural parameters from LP-estimated auxiliary parameters; counterfactual policy-path analysis subject to a Mahalanobis-distance “modesty” test; state-dependent and nonlinear LPs; and panel LP / LP-DiD for staggered-adoption settings. Worked illustrations throughout convey magnitudes without claiming new empirical results of their own: a state-dependent local-projection estimate of the OECD fiscal-consolidation multiplier (1978-2019) finds the average four-year output response is more than twice as large in slumps (-1.78, chi-squared(5)=58.3, p=0) as in booms (-0.80, chi-squared(5)=17.2, p=0.004); a projection-minimum-distance estimate of a UK Phillips curve (1975m1-2007m12, using the Cloyne-Hürtgen 2016 monetary shock) yields coefficients of 0.838 (SE 0.593) on inflation and -1.990 (SE 0.180) on the output term; and an LP-IV estimate of the unemployment response to a Romer-Romer monetary shock (1985:1-1999:12) peaks at roughly 1.25 percentage points around 24 months before returning to zero by about 48 months.

Loose Monetary Policy and Financial Instability

This paper provides the first long-run causal evidence that a persistently loose stance of monetary policy — defined as extended periods of low interest rates relative to the neutral rate — significantly raises the probability of a financial crisis several years later. Using a long historical panel of 18 advanced economies (approximately 1870–2020, excluding world wars), the paper estimates local projection (LP) regressions in which the stance is measured as the 5-year backward moving average of (r – r*), with r* from the Del Negro–Giannoni–Gaballo–Tambalotti (DGGT) factor model. The OLS baseline finds that a 1 percentage-point (pp) looser average stance over a 5-year window raises the 3-year financial crisis probability by 2.2pp at a 5–7 year horizon and 3.3pp at a 7–9 year horizon, against an unconditional base of 10.5%. To address the endogeneity of monetary policy to pre-existing economic conditions, the authors construct an instrumental variable based on the international trilemma of open-economy finance: for countries pegging their exchange rate, changes in the base-country interest rate orthogonal to domestic economic conditions provide exogenous variation in domestic rates, weighted by a capital mobility index. IV estimates are substantially larger: 1pp looser average stance raises crisis probability by 5.5pp at 5–7 years and 15.5pp at 7–9 years, indicating that OLS understates the causal effect because accommodative policy is endogenously adopted during recessions when crisis risk is already low. The same loose-policy stance significantly raises the probability of entering R-zones — periods of credit market overheating identified by Greenwood, Hanson, Shleifer, and Sørensen (2022) as harbingers of financial crisis — and, with a lag of 6–9 years, raises the probability of historically low GDP growth (below the 20th percentile of the cross-country distribution). The evidence supports a growth-risk tradeoff: loose policy may deliver short-term stimulus, but at a meaningful cost in medium-term financial fragility and real tail risk.