Olivier Blanchard

Bio: Olivier Blanchard is an academic researcher from Peterson Institute for International Economics. The author has contributed to research in topics: Unemployment & Monetary policy. The author has an hindex of 121, co-authored 385 publications receiving 72024 citations. Previous affiliations of Olivier Blanchard include International Monetary Fund & Harvard University.

The Dynamic Effects of Aggregate Demand and Supply Disturbances

Abstract: We interpret fluctuations in GNP and unemployment as due to two types of disturbances: disturbances that have a permanent effect on output and disturbances that do not. We interpret the first as supply disturbances, the second as demand disturbances. Demand disturbances have a hump-shaped mirror-image effect on output and unemployment. The effect of supply disturbances on output increases steadily over time, peaking after two years and reaching a plateau after five years.

Lectures on Macroeconomics

Abstract: Lectures on Macroeconomics provides the first comprehensive description and evaluation of macroeconomic theory in many years. While the authors' perspective is broad, they clearly state their assessment of what is important and what is not as they present the essence of macroeconomic theory today. The main purpose of Lectures on Macroeconomics is to characterize and explain fluctuations in output, unemployment and movement in prices. The most important fact of modern economic history is persistent long term growth, but as the book makes clear, this growth is far from steady. The authors analyze and explore these fluctuations. Topics include consumption and investment; the Overlapping Generations Model; money; multiple equilibria, bubbles, and stability; the role of nominal rigidities; competitive equilibrium business cycles, nominal rigidities and economic fluctuations, goods, labor and credit markets; and monetary and fiscal policy issues. Each of chapters 2 through 9 discusses models appropriate to the topic. Chapter 10 then draws on the previous chapters, asks which models are the workhorses of macroeconomics, and sets the models out in convenient form. A concluding chapter analyzes the goals of economic policy, monetary policy, fiscal policy, and dynamic inconsistency. Written as a text for graduate students with some background in macroeconomics, statistics, and econometrics, Lectures on Macroeconomics also presents topics in a self contained way that makes it a suitable reference for professional economists.

The solution of linear difference models under rational expectations

Abstract: IN HIS SURVEY ON RATIONAL EXPECTATIONS, R. Shiller indicates that the difficulty of obtaining explicit solutions for linear difference models under rational expectations may have hindered their use [14, p. 27]. The present paper attempts to remedy that problem by giving the explicit solution for an important subclass of the model Shiller refers to as the general linear difference model. Section 1 presents the form of the model for which the solution is derived and shows how particular models can be put in this form. Section 2 gives the solution together with the conditions for existence and uniqueness. 1. THE MODEL The model is given by (la), (lb), and (1c) as follows:

Debt, Deficits and Finite Horizons

Abstract: Many issues in macroeconomics, such as the level of the steady state interest rate, or the dynamic effects of government deficit finance, depend crucially on the horizon of economic agents. This paper develops a simple analytical model in which such issues can be examined and in which the horizon of agents is a parameter which can be chosen arbitrarily.The first three sections of the paper characterize the dynamics and steady state of the economy in the absence of a government. The focus is on the effects of the horizon index on the economy. The paper clarifies in particular the separate roles of finite horizons and declining labor income through life in the determination of steady state interest rates.The next three sections study the effects and the role of fiscal policy.The focus is on the effects of deficit finance both in closed and open economies. The paper clarifies the respective roles of government spending, deficits and debt in the determination of interest rates.

Bounds testing approaches to the analysis of level relationships

Abstract: This paper develops a new approach to the problem of testing the existence of a level relationship between a dependent variable and a set of regressors, when it is not known with certainty whether the underlying regressors are trend- or first-difference stationary. The proposed tests are based on standard F- and t-statistics used to test the significance of the lagged levels of the variables in a univariate equilibrium correction mechanism. The asymptotic distributions of these statistics are non-standard under the null hypothesis that there exists no level relationship, irrespective of whether the regressors are I(0) or I(1). Two sets of asymptotic critical values are provided: one when all regressors are purely I(1) and the other if they are all purely I(0). These two sets of critical values provide a band covering all possible classifications of the regressors into purely I(0), purely I(1) or mutually cointegrated. Accordingly, various bounds testing procedures are proposed. It is shown that the proposed tests are consistent, and their asymptotic distribution under the null and suitably defined local alternatives are derived. The empirical relevance of the bounds procedures is demonstrated by a re-examination of the earnings equation included in the UK Treasury macroeconometric model. Copyright © 2001 John Wiley & Sons, Ltd.

Time Series Analysis

Abstract: Any series of observations ordered along a single dimension, such as time, may be thought of as a time series. The emphasis in time series analysis is on studying the dependence among observations at different points in time. What distinguishes time series analysis from general multivariate analysis is precisely the temporal order imposed on the observations. Many economic variables, such as GNP and its components, price indices, sales, and stock returns are observed over time. In addition to being interested in the contemporaneous relationships among such variables, we are often concerned with relationships between their current and past values, that is, relationships over time.

How Much Should We Trust Differences-In-Differences Estimates?

Abstract: Most papers that employ Differences-in-Differences estimation (DD) use many years of data and focus on serially correlated outcomes but ignore that the resulting standard errors are inconsistent. To illustrate the severity of this issue, we randomly generate placebo laws in state-level data on female wages from the Current Population Survey. For each law, we use OLS to compute the DD estimate of its “effect” as well as the standard error of this estimate. These conventional DD standard errors severely understate the standard deviation of the estimators: we find an “effect” significant at the 5 percent level for up to 45 percent of the placebo interventions. We use Monte Carlo simulations to investigate how well existing methods help solve this problem. Econometric corrections that place a specific parametric form on the time-series process do not perform well. Bootstrap (taking into account the autocorrelation of the data) works well when the number of states is large enough. Two corrections based on asymptotic approximation of the variance-covariance matrix work well for moderate numbers of states and one correction that collapses the time series information into a “pre”- and “post”-period and explicitly takes into account the effective sample size works well even for small numbers of states.

The Great Crash, the Oil Price Shock, and the Unit Root Hypothesis

Abstract: We consider the null hypothesis that a time series has a unit root with possibly nonzero drift against the alternative that the process is «trend-stationary». The interest is that we allow under both the null and alternative hypotheses for the presence for a one-time change in the level or in the slope of the trend function. We show how standard tests of the unit root hypothesis against trend stationary alternatives cannot reject the unit root hypothesis if the true data generating mechanism is that of stationary fluctuations around a trend function which contains a one-time break