The Growth Effects of El Niño and La Niña: Local Weather Conditions Matter
This paper contributes to the climate-economy literature by analyzing the role of weather patterns in influencing the transmission of global climate cycles to economic growth. More specifically, we focus on El Niño Southern Oscillation (ENSO) events and their interactions with local weather conditions, taking into account the heterogeneous and cumulative effects of weather patterns on economic growth and the asymmetry and nonlinearity in the global influence of ENSO on economic activity. Using data on 75 countries over the period 1975-2014, we provide evidence for the negative growth effects ...
Nowcasting Turkish GDP and News Decomposition
Real gross domestic product (GDP) data in Turkey are released with a very long delay compared with other economies, between 10 and 13 weeks after the end of the reference quarter. To infer the current state of the economy, policy makers, media, and market practitioners examine data that are more timely, that are released at higher frequencies than the GDP. In this paper, we propose an econometric model that automatically allows us to read through these more current and higher-frequency data and translate them into nowcasts for the Turkish real GDP. Our model outperforms nowcasts produced by ...
Global Spillover Effects of US Uncertainty
We study spillover effects of US uncertainty fluctuations using panel data from fifteen emerging market economies (EMEs). A US uncertainty shock negatively affects EME stock prices and exchange rates, raises EME country spreads, and leads to capital outflows from them. Moreover, it decreases EME output, while increasing their consumer prices and net exports. The negative effects on output, exchange rates, and stock prices are weaker, but the effects on capital and trade flows stronger, for South American countries compared to other EMEs. We present a model of a small open economy that faces ...
The Importance of Updating: Evidence from a Brazilian Nowcasting Model
How often should we update predictions for economic activity? Gross domestic product is a quarterly variable disseminated usually a couple of months after the end of the quarter, but many other macroeconomic indicators are released with a higher frequency, and financial markets react very strongly to them. However, most of the professional forecasters, including the IMF, the OECD, and most central banks, tend to update their forecasts of economic activity only two to four times a year. The main exception is the Central Bank of Brazil which is responsible for collecting and publishing a daily ...
The Evolution of Health over the Life Cycle
We construct a unified objective measure of health status: the frailty index, defined as the cumulative sum of all adverse health indicators observed for an individual. First, we show that the frailty index has several advantages over self-reported health status, particularly when studying health dynamics. Then we estimate a stochastic process for frailty dynamics over the life cycle. We find that the autocovariance structure of frailty in panel data strongly supports a process that allows the conditional variance of frailty shocks to increase with age. Our frailty measure and dynamic process ...
Exploiting the monthly data flow in structural forecasting
This paper develops a framework that allows us to combine the tools provided by structural models for economic interpretation and policy analysis with those of reduced-form models designed for nowcasting. We show how to map a quarterly dynamic stochastic general equilibrium (DSGE) model into a higher frequency (monthly) version that maintains the same economic restrictions. Moreover, we show how to augment the monthly DSGE with auxiliary data that can enhance the analysis and the predictive accuracy in now-casting and forecasting. Our empirical results show that both the monthly version of ...
Measuring Uncertainty and Its Impact on the Economy
We propose a new framework for measuring uncertainty and its effects on the economy, based on a large VAR model with errors whose stochastic volatility is driven by two common unobservable factors, representing aggregate macroeconomic and financial uncertainty. The uncertainty measures can also influence the levels of the variables so that, contrary to most existing measures, ours reflect changes in both the conditional mean and volatility of the variables, and their impact on the economy can be assessed within the same framework. Moreover, identification of the uncertainty shocks is ...
Thousands of models, one story: current account imbalances in the global economy
The global financial crisis has led to a revival of the empirical literature on current account imbalances. This paper contributes to that literature by investigating the importance of evaluating model and parameter uncertainty prior to reaching any firm conclusion. We explore three alternative econometric strategies: examining all models, selecting a few, and combining them all. Out of thousands (or indeed millions) of models a story emerges. The chance that current accounts were aligned with fundamentals prior to the financial crisis appears to be minimal.
FRED-QD: A Quarterly Database for Macroeconomic Research
In this article, we present and describe FRED-QD, a large, quarterly frequency macroeconomic database that is currently available and regularly updated at https://research.stlouisfed.org/econ/mccracken/fred-databases/. The data provided are closely modeled to that used in Stock and Watson (2012a). As in our previous work on FRED-MD (McCracken and Ng, 2016), which is at a monthly frequency, our goal is simply to provide a publicly available source of macroeconomic "big data" that is updated in real time using the FRED® data service. We show that factors extracted from the FRED-QD dataset ...
Priors for the long run
We propose a class of prior distributions that discipline the long-run predictions of vector autoregressions (VARs). These priors can be naturally elicited using economic theory, which provides guidance on the joint dynamics of macroeconomic time series in the long run. Our priors for the long run are conjugate, and can thus be easily implemented using dummy observations and combined with other popular priors. In VARs with standard macroeconomic variables, a prior based on the long-run predictions of a wide class of theoretical models yields substantial improvements in the forecasting ...