Institute of Applied Economics
3000, chemin de la Cote-Sainte-Catherine
Montreal, Quebec H3T 2A7
Institutional Affiliation: HEC Montreal
Information about this author at RePEc
NBER Working Papers and Publications
|August 2020||Trade Flows and Fiscal Multipliers|
with : w27652
We present novel insights on the role of international trade following unanticipated government spending and income tax changes in a flexible exchange rate environment. In a simple two-country, two-good model, we show analytically that fiscal multipliers can be larger in economies more open to trade, even when fiscal expansions imply a trade deficit. Cross-country comovement can be positive or negative. Three factors determine how trade linkages affect fiscal multipliers: the relative import share of public and private goods, how the government finances its budget, and the currency invoicing of exports. A Bayesian prior-predictive analysis shows a quantitative international business-cycle model bears the same predictions. Estimating the model on Canadian and U.S. data, we find support for ...
|July 2015||Clearing Up the Fiscal Multiplier Morass: Prior and Posterior Analysis|
with , : w21433
We use Bayesian prior and posterior analysis of a monetary DSGE model, extended to include fiscal details and two distinct monetary-fiscal policy regimes, to quantify government spending multipliers in U.S. data. The combination of model specification, observable data, and relatively diffuse priors for some parameters lands posterior estimates in regions of the parameter space that yield fresh perspectives on the transmission mechanisms that underlie government spending multipliers. Posterior mean estimates of short-run output multipliers are comparable across regimes—about 1.4 on impact—but much larger after 10 years under passive money/active fiscal than under active money/passive fiscal—means of 1.9 versus 0.7 in present value.
Published: Eric M. Leeper & Nora Traum & Todd B. Walker, 2017. "Clearing Up the Fiscal Multiplier Morass," American Economic Review, vol 107(8), pages 2409-2454.
|September 2011||Clearing Up the Fiscal Multiplier Morass|
with , : w17444
Bayesian prior predictive analysis of five nested DSGE models suggests that model specifications and prior distributions tightly circumscribe the range of possible government spending multipliers. Multipliers are decomposed into wealth and substitution effects, yielding uniform comparisons across models. By constraining the multiplier to tight ranges, model and prior selections bias results, revealing less about fiscal effects in data than about the lenses through which researchers choose to interpret data. When monetary policy actively targets inflation, output multipliers can exceed one, but investment multipliers are likely to be negative. Passive monetary policy produces consistently strong multipliers for output, consumption, and investment.
Published: Eric M. Leeper & Nora Traum & Todd B. Walker, 2017. "Clearing Up the Fiscal Multiplier Morass," American Economic Review, vol 107(8), pages 2409-2454. citation courtesy of
|July 2009||Dynamics of Fiscal Financing in the United States|
with , : w15160
Dynamic stochastic general equilibrium models that include policy rules for government spending, lump-sum transfers, and distortionary taxation on labor and capital income and on consumption expenditures are fit to U.S. data under a variety of specifications of fiscal policy rules. We obtain several results. First, the best fitting model allows a rich set of fiscal instruments to respond to stabilize debt. Second, responses of aggregate variables to fiscal policy shocks under rich fiscal rules can vary considerably from responses that allow only non-distortionary fiscal instruments to finance debt. Third, based on estimated policy rules, transfers, capital tax rates, and government spending have historically responded strongly to government debt, while labor taxes have responded more weakl...
Published: Leeper, Eric M. & Plante, Michael & Traum, Nora, 2010.
"Dynamics of fiscal financing in the United States,"
Journal of Econometrics,
Elsevier, vol. 156(2), pages 304-321, June.
citation courtesy of