Dynamic Factor Models, Cointegration, and Error Correction Mechanisms
The paper studies Non-Stationary Dynamic Factor Models such that: (1) the factors Ft are I(1) and singular, i.e. Ft has dimension r and is driven by a q-dimensional white noise, the common shocks, with q < r, and (2) the idiosyncratic components are I(1). We show that Ft is driven by r-c permanent shocks, where c is the cointegration rank of Ft, and q - (r - c) < c transitory shocks, thus the same result as in the non-singular case for the permanent shocks but not for the transitory shocks. Our main result is obtained by combining the classic Granger Representation Theorem with recent ...
Non-Stationary Dynamic Factor Models for Large Datasets
We study a Large-Dimensional Non-Stationary Dynamic Factor Model where (1) the factors Ft are I (1) and singular, that is Ft has dimension r and is driven by q dynamic shocks with q less than r, (2) the idiosyncratic components are either I (0) or I (1). Under these assumption the factors Ft are cointegrated and modeled by a singular Error Correction Model. We provide conditions for consistent estimation, as both the cross-sectional size n, and the time dimension T, go to infinity, of the factors, the loadings, the shocks, the ECM coefficients and therefore the Impulse Response Functions. ...
Common Factors, Trends, and Cycles in Large Datasets
This paper considers a non-stationary dynamic factor model for large datasets to disentangle long-run from short-run co-movements. We first propose a new Quasi Maximum Likelihood estimator of the model based on the Kalman Smoother and the Expectation Maximisation algorithm. The asymptotic properties of the estimator are discussed. Then, we show how to separate trends and cycles in the factors by mean of eigenanalysis of the estimated non-stationary factors. Finally, we employ our methodology on a panel of US quarterly macroeconomic indicators to estimate aggregate real output, or Gross ...
Bias in Local Projections
Local projections (LPs) are a popular tool in applied macroeconomic research. We survey the related literature and find that LPs are often used with very small samples in the time dimension. With small sample sizes, given the high degree of persistence in most macroeconomic data, impulse responses estimated by LPs can be severely biased. This is true even if the right-hand-side variable in the LP is iid, or if the data set includes a large cross-section (i.e., panel data). We derive a simple expression to elucidate the source of the bias. Our expression highlights the interdependence between ...
Some International Evidence for Keynesian Economics Without the Phillips Curve
Farmer and Nicol (2018) show that the Farmer Monetary (FM)-model outperforms the three-equation New-Keynesian (NK)-model in post war U.S. data. In this paper, we compare the marginal data density of the FM-model with marginal data densities for determinate and indeterminate versions of the NK-model for three separate samples using U.S., U.K. and Canadian data. We estimate versions of both models that restrict the parameters of the private sector equations to be the same for all three countries. Our preferred specification is the constrained version of the FM-model which has a marginal data ...
Employment Effects of Unconventional Monetary Policy : Evidence from QE
This paper investigates the effect of the Federal Reserve's unconventional monetary policy on employment via a bank lending channel. We find that banks with higher mortgage-backed securities holdings issued relatively more loans after the first and third rounds of quantitative easing (QE1 and QE3). While additional volume is concentrated in refinanced mortgages after QE1, increases are driven by newly originated home purchase mortgages and additional commercial and industrial lending after QE3. Using spatial variation, we show that regions with a high share of affected banks experienced ...
Persistence Dependence in Empirical Relations: The Velocity of Money
Standard theory predicts persistence dependence in numerous economic relationships. (For example, persistence dependence is precisely the kind of nonlinear relationship posited in the Permanent Income Hypothesis; persistence dependence is the inverse of ?frequency dependence? in a relationship.) Until recently, however, it was challenging to achieve credible inference about persistence dependence in an economic relationship using available methods. However, recently developed econometric tools (Ashley and Verbrugge, 2009a) allow one to elegantly quantify the variation in a time-series ...
Database of global economic indicators (DGEI): a methodological note
The Database of Global Economic Indicators (DGEI) from the Federal Reserve Bank of Dallas is aimed at standardizing and disseminating world economic indicators for policy analysis and scholarly work on the role of globalization. The purpose of DGEI is to offer a broad perspective on how economic developments around the world influence the U.S. economy with a wide selection of indicators. DGEI is automated within an Excel-VBA and E-views framework for the processing and aggregation of multiple country time series. It includes a core sample of 40 countries with available indicators and broad ...
Human Capital and Development
Perhaps no question has attracted as much attention in the economics literature as ?Why are some countries richer than others?? In this article, the author revisits the ?development problem? and provides some estimates of the importance of human capital in accounting for cross-country differences in output per worker. His results suggest that human capital has a central role in determining the wealth of nations and that the quality of human capital varies systematically with the level of development.
The Fed's Asymmetric Forecast Errors
I show that the probability that the Board of Governors of the Federal Reserve System staff's forecasts (the "Greenbooks'") overpredicted quarterly real gross domestic product (GDP) growth depends on both the forecast horizon and also whether the forecasted quarter was above or below trend real GDP growth. For forecasted quarters that grew below trend, Greenbooks were much more likely to overpredict real GDP growth, with one-quarter ahead forecasts overpredicting real GDP growth more than 75% of the time, and this rate of overprediction was higher for further ahead forecasts. For forecasted ...