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  • 1
    Publication Date: 2019-02-16
    Description: Although the influence of exceptional weather on individual behaviour has already been acknowledged in finance, psychology, and marketing, the literature examining weather effects at more aggregate level is still limited. Further, there is a lot of anecdotal evidence that weather anomalies affect consumer spending and retail business. The main aim of this analysis is to investigate and quantify the effects of unusual weather in consumer spending at macro-level. Using aggregate retail sales data for Switzerland, our findings reveal that weather deviations from seasonal norms, especially, unusually high or low temperatures in a given month, do cause sizeable intertemporal shifts in consumer spending at country level. Furthermore, the effects of abnormal weather are found to differ across seasons, both with respect to sign and magnitude. In particular, our findings indicate that weather effects manifest mainly through the seasons change channel: weather conditions in line with the coming season boost the purchases early in the season.
    Keywords: E21 ; E32 ; D12 ; C22 ; ddc:330 ; Consumer spending ; intertemporal shifts ; retail sales ; unusual weather
    Repository Name: EconStor: OA server of the German National Library of Economics - Leibniz Information Centre for Economics
    Language: English
    Type: doc-type:workingPaper
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  • 2
    Publication Date: 2019-03-13
    Description: This paper performs a comparative analysis of estimation as well as of out-of-sample forecasting results of more than 20 estimators common in the panel data literature using the data on migration to Germany from 18 source countries in the period 1967-2001. Our results suggest that the choice of an estimation procedure has a substantial impact on the parameter estimates of the migration function. Out-of-sample forecasting results indicate the following: (i) the standard fixed effects estimators clearly outperforms the pooled OLS estimator, (ii) both the fixed effects estimators and the hierarchical Bayes estimator exhibit the superior forecast performance, (iii) the fixed effects estimators outperform GMM and other instrumental variables estimators, (iv) forecasting performance of heterogenous estimators is mediocre in our data set.
    Keywords: C23 ; C53 ; F22 ; ddc:330 ; international migration ; panel data ; forecasting ; Internationale Wanderung ; Prognoseverfahren ; Schätztheorie ; Panel ; Deutschland
    Repository Name: EconStor: OA server of the German National Library of Economics - Leibniz Information Centre for Economics
    Language: English
    Type: doc-type:workingPaper
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  • 3
    Publication Date: 2019-03-13
    Description: This study utilizes the dynamic factor model of Giannone et al. (2008) in order to make now-/forecasts of GDP quarter-on-quarter growth rates in Switzerland. It also assesses the informational content of macroeconomic data releases for forecasting of the Swiss GDP. We find that the factor model offers a substantial improvement in forecast accuracy of GDP growth rates compared to a benchmark naive constant-growth model at all forecast horizons and at all data vintages. The largest forecast accuracy is achieved when GDP nowcasts for an actual quarter are made about three months ahead of the official data release. We also document that both business tendency surveys as well as stock market indices possess the largest informational content for GDP forecasting although their ranking depends on the underlying transformation of monthly indicators from which the common factors are extracted.
    Keywords: C53 ; E37 ; ddc:330 ; Business tendency surveys ; Forecasting ; Nowcasting ; Real-time data ; Dynamic factor model ; Konjunkturprognose ; Prognoseverfahren ; Geschäftsklima ; Faktorenanalyse ; Schätzung ; Schweiz
    Repository Name: EconStor: OA server of the German National Library of Economics - Leibniz Information Centre for Economics
    Language: English
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  • 4
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    Hamburg: Hamburg University, Department Economics and Politics
    Publication Date: 2020-01-22
    Description: Based on annual data for growth and inflation forecasts for Germany covering the time span from 1970 to 2007 and up to 17 different forecasts per year, we test for a possible asymmetry of the forecasters' loss function and estimate the degree of asymmetry for each forecasting institution using the approach of Elliot et al. (2005). Furthermore, we test for the rationality of the forecasts under the assumption of a possibly asymmetric loss function and for the features of an optimal forecast under the assumption of a generalized loss function. We find only limited evidence for the existence of an asymmetric loss functions of German forecasters. As regards the rationality of the forecasts the results depend on the underlying assumption of the test. The rationality of inflation forecasts is more doubtful than those of growth forecasts.
    Keywords: C53 ; E42 ; ddc:330 ; Business cycle forecast evaluation ; asymmetric loss function ; and rational expectations
    Repository Name: EconStor: OA server of the German National Library of Economics - Leibniz Information Centre for Economics
    Language: English
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  • 5
    Publication Date: 2019-08-14
    Description: In this paper, we make multi-step forecasts of the annual growth rates of the real GDP for each of the 16 German Länder (states) simultaneously. Beside the usual panel data models, such as pooled and fixed-effects models, we apply panel models that explicitly account for spatial dependence between regional GDP. We find that both pooling and accounting for spatial effects helps substantially improve the forecast performance compared to the individual autoregressive models estimated for each of the L¨ander separately. More importantly, we have demonstrated that effect of accounting for spatial dependence is even more pronounced at longer forecasting horizons (the forecast accuracy gain as measured by the root mean squared forecast error is about 9% at 1-year horizon and exceeds 40% at 5-year horizon). Hence, we strongly recommend incorporating spatial dependence structure into regional forecasting models, especially, when long-term forecasts are made.
    Description: Corrected version, December 17, 2007
    Keywords: C21 ; C53 ; C23 ; ddc:330 ; German Länder ; forecasting ; dynamic panel model ; spatial autocorrelation
    Repository Name: EconStor: OA server of the German National Library of Economics - Leibniz Information Centre for Economics
    Language: English
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  • 6
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    Seville: European Commission, Joint Research Centre (JRC)
    Publication Date: 2019-08-28
    Description: The present paper estimates and decomposes the employment effect of innovation by R&D intensity levels. Our microeconometric analysis is based on a large international panel data set from the EU Industrial R&D Investment Scoreboard. Employing flexible semi-parametric methods - the generalised propensity score - allows us to recover the full functional relationship between R&D investment and firm employment, and to address important econometric issues, which is not possible in the standard estimation approach used in the previous literature. Our results suggest that modest innovators do not create and may even destruct jobs by raising their R&D expenditures. Most of the jobs in the economy are created by innovation followers: increasing innovation by 1% may increase employment up to 0.7%. The job creation effect of innovation reaches its peak when R&D intensity is around 100% of the total capital expenditure, after which the positive employment effect declines and becomes statistically insignificant. Innovation leaders do not create jobs by further increasing their R&D expenditures, which are already very high.
    Keywords: C14 ; C21 ; F23 ; J20 ; J23 ; O30 ; O32 ; O33 ; ddc:330 ; Innovation ; R&D investment ; causal inference ; semi-parametric ; employment ; job creation ; GPS
    Repository Name: EconStor: OA server of the German National Library of Economics - Leibniz Information Centre for Economics
    Language: English
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  • 7
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    Ispra: European Commission, Joint Research Centre (JRC)
    Publication Date: 2019-08-28
    Description: We provide a novel evidence about the innovation-employment nexus by decomposing it by R&D intensity in a continuous setup and relaxing the linearity assumption. Using a large international firm-level panel data set for OECD countries and employing a flexible semi-parametric method – the generalised propensity score – allows us to recover the full functional relationship between the R&D-driven innovation and firm employment as well as address important econometric issues, which is not possible in the standard estimation approach used in the previous literature. Our results confirm that the relationship between innovation and employment entails important non-linearities responsible for significant differences in employment response to innovation at different R&D intensity levels.
    Keywords: C14 ; C21 ; F23 ; J20 ; J23 ; O30 ; O32 ; O33 ; ddc:330 ; R&D investment ; employment ; propensity score ; firm-level data
    Repository Name: EconStor: OA server of the German National Library of Economics - Leibniz Information Centre for Economics
    Language: English
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  • 8
    Publication Date: 2019-03-13
    Description: In this paper, we investigate whether the Google search activity can help in nowcasting the year-on-year growth rates of monthly US private consumption using a real-time data set. The Google-based forecasts are compared to those based on a benchmark AR(1) model and the models including the consumer surveys and financial indicators. According to the Diebold-Mariano test of equal predictive ability, the null hypothesis can be rejected suggesting that Google-based forecasts are significantly more accurate than those of the benchmark model. At the same time, the corresponding null hypothesis cannot be rejected for models with consumer surveys and financial variables. Moreover, when we apply the test of superior predictive ability (Hansen, 2005) that controls for possible data-snooping biases, we are able to reject the null hypothesis that the benchmark model is not inferior to any alternative model forecasts. Furthermore, the results of the model confidence set (MCS) procedure (Hansen et al., 2005) suggest that the autoregressive benchmark is not selected into a set of the best forecasting models. Apart from several Google-based models, the MCS contains also some models including survey-based indicators and financial variables. We conclude that Google searches do help improving the nowcasts of the private consumption in US.
    Keywords: C22 ; C53 ; C82 ; ddc:330 ; Google indicators ; real-time nowcasting ; principal components ; US private consumption ; Gesamtwirtschaftlicher Konsum ; Prognoseverfahren ; Suchmaschine ; Informationsverhalten ; Konsumentenverhalten ; USA
    Repository Name: EconStor: OA server of the German National Library of Economics - Leibniz Information Centre for Economics
    Language: English
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  • 9
    Publication Date: 2018-11-29
    Description: We investigate whether the KOF Economic Barometer - a leading indicator released by the KOF Swiss Economic Institute - is useful for short-term prediction of quarterly year-on-year real GDP growth in Switzerland. Using a real-time data set consisting of historical vintages of GDP data and the leading indicator we find that the model augemented with the KOF Barometer produces more accurate forecasts of the Swiss GDP than purely autoregressive models and consensus forecasts.
    Keywords: C53 ; C22 ; ddc:330 ; Leading indicators ; forecasting ; Switzerland
    Repository Name: EconStor: OA server of the German National Library of Economics - Leibniz Information Centre for Economics
    Language: English
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  • 10
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    Leuven: Katholieke Universiteit Leuven, LICOS Centre for Institutions and Economic Performance
    Publication Date: 2019-02-04
    Description: The present paper studies the relationship between R&D investment and firm productivity growth by explicitly accounting for non-linearities in the R&D-productivity relationship and inter-sectoral firm heterogeneity. In order to address these issues, we employ a two step estimation approach, and match two firm-level panel data sets for the OECD countries, which allows us to relax both the linearity and homogeneity assumptions of the canonical Griliches (1979) knowledge capital model. Our results suggest that: (i) R&D investment increases firm productivity with an average elasticity of 0.15; (ii) the impact of R&D investment on firm productivity is differential at different levels of R&D intensity - the productivity elasticity ranges from -0.02 for low levels of R&D intensity to 0.33 for high levels of R&D intensity; (iii) the relationship between R&D expenditures and productivity growth is non-linear, and only after a certain critical mass of R&D is reached, the productivity growth is significantly positive;(iv) there are important inter-sectoral differences with respect to R&D investment and firm productivity - high-tech sectors' firms not only invest more in R&D, but also achieve more in tfirms of productivity gains connected with research activities.
    Keywords: C14 ; C21 ; D24 ; F23 ; O32 ; ddc:330 ; R&D investment ; firm productivity ; generalised propensity score
    Repository Name: EconStor: OA server of the German National Library of Economics - Leibniz Information Centre for Economics
    Language: English
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