Forecasting exports across Europe
What are the superior survey indicators
Bibliographic Data
| ID | 21541491 |
|---|---|
| Authors | Robert Lehmann (0000-0001-6684-7536, Ifo Institute for Economic Research, corresponding author) |
| Year | 2021 |
| Volume | 60 |
| Issue | 5 |
| Pages | 2429-2453 |
| Publication date | 2021-05-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Empirical Economics (JOURNAL) |
| Journal identifiers | ISSN: 0377-7332 • E-ISSN: 1435-8921 |
| Publisher | Springer Science and Business Media LLC (PUBLISHER) |
| DOI | 10.1007/s00181-020-01838-y |
| OpenAlex | W2997846811 |
| Language | EN |
| Citations received | 3 |
| References cited | 18 |
In this study, we systematically evaluate the potential of a bunch of survey-based indicators from different economic branches to forecasting export growth across a multitude of European countries. Our pseudo-out-of-sample analyses reveal that the best performing indicators beat a well-specified benchmark model in terms of forecast accuracy. It turns out that four indicators are superior: the Export Climate, the Production Expectations of domestic manufacturing firms, the Industrial Confidence Indicator, and the Economic Sentiment Indicator. Two robustness checks confirm these results. As exports are highly volatile and turn out to be a large demand-side component of gross domestic product, our results can be used by applied forecasters in order to choose the best performing indicators and thus increasing the accuracy of export forecasts
Econometrics · Economic forecasting · Economic indicator · Economics · Gross domestic product · Industrial production · Macroeconomics · Global trade and economics · Market Dynamics and Volatility · Monetary Policy and Economic Impact
| Citations per year | 0.6 |
|---|---|
| Citation span | 2021 - 2022 (2) |
| Highly cited | No |