Foreign Capacity Utilisation and German Exports of Capital Goods

Jannsen, Nils; Richter, J.

doi:10.1007/s10273-012-1464-2

Cited by 5 publications

(4 citation statements)

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“…However, studies analyzing German trade forecasts are scarce. The existing studies concentrate on forecasting a single trade aggregate, i.e., German exports (Elstner et al 2013;Grossmann and Scheufele 2019;Jannsen and Richter 2012), or imports (Grimme et al 2019;Hetemäki and Mikkola 2005). However, despite the fact that suboptimal trade forecasts can potentially be costly if, for instance, a protectionist trade policy is pursued due to such forecasts, the evaluation of trade forecasts has not received much attention.…”

Section: Introductionmentioning

confidence: 99%

A Nonparametric Evaluation of the Optimality of German Export and Import Growth Forecasts under Flexible Loss

Behrens

2019

Economies

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This study contributes to research on the nonparametric evaluation of German trade forecasts. To this end, I compute random classification and regression forests to analyze the optimality of annual German export and import growth forecasts from 1970 to 2017. A forecast is considered as optimal if a set of predictors, which models the information set of a forecaster at the time of forecast formation, has no explanatory power for the corresponding (sign of the) forecast error. I analyze trade forecasts of four major German economic research institutes, a collaboration of German economic research institutes, and one international forecaster. For trade forecasts with a horizon of half-a-year, I cannot reject forecast optimality for all but one forecaster. In the case of a forecast horizon of one year, forecast optimality is rejected in more cases if the underlying loss function is assumed to be quadratic. Allowing for a flexible loss function results in more favorable assessment of forecast optimality.

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Section: Introductionmentioning

confidence: 99%

A Nonparametric Evaluation of the Optimality of German Export and Import Growth Forecasts under Flexible Loss

Behrens

2019

Economies

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“…As argued by Hanslin Grossmann and Scheufele (2019), this proxy can be based on survey results as well. The Kiel Institute for the World Economy (IfW) proposed a Weighted Foreign Capacity Indicator to forecasting German investment goods exports (IFWCAP; see Jannsen and Richter 2012). We adopt their idea and calculate the capacity-based indicator for all European countries in our sample.…”

Section: Potential Export Leading Indicatorsmentioning

confidence: 99%

“…Additionally, two German studies exist. Jannsen and Richter (2012) use a capacity utilization weighted indicator obtained from major export partners to forecast German capital goods exports. Elstner et al (2013) and use hard data (for example, foreign new orders in manufacturing) as well as indicators from the ifo business survey (for example, ifo Export Expectations) to improve forecasts for German exports.…”

Section: Introductionmentioning

confidence: 99%

Forecasting exports across Europe: What are the superior survey indicators?

Lehmann

2020

Empir Econ

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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.

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“…Chudik, Grossman, and Pesaran () also find that PMIs are useful for output forecasts in an international context using the global vector autoregressive model (GVAR) methodology, especially for nowcasting (but less for longer forecast horizons). Survey‐based indicators, such as the (“Information und Forschung”—Institute for Economic Research) export climate indicator (Elstner, Grimme, & Haskamp, ) or foreign capacity utilization (Jannsen & Richter, ) have also been found to be successful short‐term indicators for exports.…”

Section: Introductionmentioning

confidence: 99%

PMIs: Reliable indicators for exports?

Grossmann

Scheufele

2019

Rev International Economics

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Foreign economic activity is a major determinant of export developments. However, foreign GDP figures are published too late to be useful for short‐term forecasting. This paper presents a number of indicators based on the widely available PMI surveys that provide very early signals of foreign activity. Using MIDAS models we analyze the in‐ and out‐of‐sample performance of these and related indicators for two very trade‐exposed countries (Germany and Switzerland). We find that the monthly indicators based on foreign PMIs are strongly correlated with quarterly export growth. The forecast comparison shows that PMI‐based indicators perform very well relative to other benchmark models.

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Foreign Capacity Utilisation and German Exports of Capital Goods

Cited by 5 publications

References 0 publications

A Nonparametric Evaluation of the Optimality of German Export and Import Growth Forecasts under Flexible Loss

A Nonparametric Evaluation of the Optimality of German Export and Import Growth Forecasts under Flexible Loss

Forecasting exports across Europe: What are the superior survey indicators?

PMIs: Reliable indicators for exports?

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