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Displaying results 1 to 22 of 22.

  1. Overfitting in judgment-based economic forecasts
    the case of IMF growth projections
    Author: Hellwig, Klaus-Peter
    Published: 2018
    Publisher:  International Monetary Fund, [Washington, D.C.]

    I regress real GDP growth rates on the IMF's growth forecasts and find that IMF forecasts behave similarly to those generated by overfitted models, placing too much weight on observable predictors and underestimating the forces of mean reversion. I... more

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    Orient-Institut Beirut
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    I regress real GDP growth rates on the IMF's growth forecasts and find that IMF forecasts behave similarly to those generated by overfitted models, placing too much weight on observable predictors and underestimating the forces of mean reversion. I identify several such variables that explain forecasts well but are not predictors of actual growth. I show that, at long horizons, IMF forecasts are little better than a forecasting rule that uses no information other than the historical global sample average growth rate (i.e., a constant). Given the large noise component in forecasts, particularly at longer horizons, the paper calls into question the usefulness of judgment-based medium and long-run forecasts for policy analysis, including for debt sustainability assessments, and points to statistical methods to improve forecast accuracy by taking into account the risk of overfitting

     
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  2. Similarities in the USDA international baseline projections
    Author: Chandio, Rabail; Katchova, Ani L.
    Published: [2024]
    Publisher:  Center for Agricultural and Rural Development, Ames, Iowa

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    ZBW - Leibniz-Informationszentrum Wirtschaft, Standort Kiel
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    Language: English
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    Series: Working paper / Center for Agricultural and Rural Development ; 24-WP 661 (July 2024)
    Subjects: agricultural baselines; USDA baselines; commodity projections; forecast evaluation
    Scope: 1 Online-Ressource (circa 24 Seiten)
  3. On the comparison of interval forecasts
    Author: Askanazi, Ross; Diebold, Francis X.; Schorfheide, Frank; Shin, Minchul
    Published: August 2, 2018
    Publisher:  Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, Philadelphia, PA

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    Source: Union catalogues
    Language: English
    Media type: Book
    Format: Online
    Series: PIER working paper ; 18, 013
    Subjects: Forecast accuracy; forecast evaluation; prediction
    Scope: 1 Online-Ressource (circa 23 Seiten)
  4. A benchmark model for fixed-target Arctic Sea ice forecasting
    Author: Diebold, Francis X.; Göbel, Maximilian
    Published: January 2, 2022
    Publisher:  Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, Philadelphia, PA

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    Language: English
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    Series: PIER working paper ; 22, 002
    Subjects: Climate forecasting; climate prediction; climate change; forecast evaluation
    Scope: 1 Online-Ressource (circa 13 Seiten), Illustrationen
  5. Nowcasting the state of the Italian economy
    the role of financial markets
    Author: Ceci, Donato; Silvestrini, Andrea
    Published: [2022]
    Publisher:  Banca d'Italia Eurosistema, [Rom]

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    Series: Temi di discussione / Banca d'Italia ; number 1362 (February 2022)
    Subjects: financial markets; probit models; factor-augmented probit models; model confidence set; penalized likelihood; forecast evaluation
    Scope: 1 Online-Ressource (circa 61 Seiten), Illustrationen
  6. Forecasting with panel data
    estimation uncertainty versus parameter heterogeneity
    Author: Pesaran, M. Hashem; Pick, Andreas; Timmermann, Allan
    Published: April 2022
    Publisher:  CESifo, Center for Economic Studies & Ifo Institute, Munich, Germany

    We develop novel forecasting methods for panel data with heterogeneous parameters and examine them together with existing approaches. We conduct a systematic comparison of their predictive accuracy in settings with different cross-sectional (N) and... more

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    We develop novel forecasting methods for panel data with heterogeneous parameters and examine them together with existing approaches. We conduct a systematic comparison of their predictive accuracy in settings with different cross-sectional (N) and time (T) dimensions and varying degrees of parameter heterogeneity. We investigate conditions under which panel forecasting methods can perform better than forecasts based on individual estimates and demonstrate how gains in predictive accuracy depend on the degree of parameter heterogeneity, whether heterogeneity is correlated with the regressors, the goodness of fit of the model, and, particularly, the time dimension of the data set. We propose optimal combination weights for forecasts based on pooled and individual estimates and develop a novel forecast poolability test that can be used as a pretesting tool. Through a set of Monte Carlo simulations and three empirical applications to house prices, CPI inflation, and stock returns, we show that no single forecasting approach dominates uniformly. However, forecast combination and shrinkage methods provide better overall forecasting performance and offer more attractive risk profiles compared to individual, pooled, and random effects methods.

     
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    Source: Union catalogues
    Language: English
    Media type: Book
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    hdl: 10419/260820
    Series: CESifo working paper ; no. 9690 (2022)
    Subjects: forecasting; panel data; heterogeneity; forecast evaluation; forecast combination; shrinkage; pooling
    Scope: 1 Online-Ressource (circa 61 Seiten), Illustrationen
  7. Can information on the distribution of ZAR returns be used to improve SARB's ZAR forecasts?
    Author: Greenwood-Nimmo, Matthew; Steenkamp, Daan; Van Jaarsveld, Rossouw
    Published: 27 September 2022
    Publisher:  Economic Research and Statistics Department, South African Reserve Bank, Pretoria

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    ZBW - Leibniz-Informationszentrum Wirtschaft, Standort Kiel
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    Series: South African Reserve Bank working paper series ; WP, 22, 14
    Subjects: Foreign exchange markets; realised and options-implied return distributions; variance risk premium; forecast evaluation
    Scope: 1 Online-Ressource (circa 27 Seiten), Illustrationen
  8. How Credit Improves the Exchange Rate Forecast
    Author: Časta, Martin
    Published: August 2022
    Publisher:  Czech National Bank, Economic Research Department, Praha

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    ZBW - Leibniz-Informationszentrum Wirtschaft, Standort Kiel
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    Series: Working paper series / Czech National Bank ; 2022, 7
    Subjects: Exchange rates; forecasting; forecast evaluation
    Scope: 1 Online-Ressource (circa 42 Seiten), Illustrationen
  9. Recessions as breadwinner for forecasters state-dependent evaluation of predictive ability: evidence from big macroeconomic US data
    Author: Siliverstovs, Boriss; Wochner, Daniel S.
    Published: 2020
    Publisher:  Latvijas Banka, Riga

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    Source: Union catalogues
    Language: English
    Media type: Ebook
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    ISBN: 9789934578236
    Series: Working paper / Latvijas Banka ; 2020,2
    Subjects: forecast evaluation; dynamic factor models; business cycle asymmetries; big macroeconomic datasets; US
    Scope: 1 Online-Ressource (circa 46 Seiten), Illustrationen
  10. Testing forecast rationality for measures of central tendency
    Author: Dimitriadis, Timo; Patton, Andrew J.; Schmidt, Patrick W.
    Published: 12/2020
    Publisher:  University of Hohenheim, Dean's Office of the Faculty of Business, Economics and Social Sciences, Stuttgart, Germany

    Rational respondents to economic surveys may report as a point forecast any measure of the central tendency of their (possibly latent) predictive distribution, for example the mean, median, mode, or any convex combination thereof. We propose tests of... more

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    ZBW - Leibniz-Informationszentrum Wirtschaft, Standort Kiel
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    Kommunikations-, Informations- und Medienzentrum der Universität Hohenheim
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    Rational respondents to economic surveys may report as a point forecast any measure of the central tendency of their (possibly latent) predictive distribution, for example the mean, median, mode, or any convex combination thereof. We propose tests of forecast rationality when the measure of central tendency used by the respondent is unknown. We overcome an identification problem that arises when the measures of central tendency are equal or in a local neighborhood of each other, as is the case for (exactly or nearly) symmetric distributions. As a building block, we also present novel tests for the rationality of mode forecasts. We apply our tests to survey forecasts of individual income, Greenbook forecasts of U.S. GDP, and random walk forecasts for exchange rates. We find that the Greenbook and random walk forecasts are best rationalized as mean, or near-meanforecasts, while the income survey forecasts are best rationalized as mode forecasts.

     
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    hdl: 10419/225630
    Series: Hohenheim discussion papers in business, economics and social sciences ; 2020, 12
    Subjects: Prognose; Prognosemodell; forecast evaluation; weak identification; survey forecasts; mode forecasts
    Scope: 1 Online-Ressource (73 Seiten), Diagramme
  11. Combining multivariate volatility forecasts using weighted losses
    Author: Clements, Adam; Doolan, M. B.
    Published: [2018]
    Publisher:  [National Centre for Econometric Research], [Brisbane]

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    ZBW - Leibniz-Informationszentrum Wirtschaft, Standort Kiel
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    Source: Union catalogues
    Language: English
    Media type: Book
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    Series: [NCER working paper series ; [#119]
    Subjects: Multivariate volatility; combination forecasts; forecast evaluation; model confidence set
    Scope: 1 Online-Ressource (circa 25 Seiten), Illustrationen
  12. A BVAR model for forecasting Ukrainian inflation
    Author: Shapovalenko, Nadiia
    Published: March 2021
    Publisher:  Graduate Institute of International and Development Studies, International Economics Department, Geneva, Switzerland

    In this paper, I examine the forecasting performance of a Bayesian Vector Autoregression (BVAR) model with steady-state prior and compare the accuracy of the forecasts against the forecasts of QPM model and official NBU forecasts over the period... more

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    In this paper, I examine the forecasting performance of a Bayesian Vector Autoregression (BVAR) model with steady-state prior and compare the accuracy of the forecasts against the forecasts of QPM model and official NBU forecasts over the period 2016q1-2020q1. My findings suggest that inflation forecasts produced by the BVAR model are more accurate than those of the QPM model two quarters ahead and are competitive for the longer horizon. For GDP growth, the forecasts of the BVAR outperform those of the QPM for the whole forecast horizon. For inflation they also outperform the official NBU forecasts over the monetary policy horizon, whereas the opposite is true for the forecasts of the GDP growth.

     
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    Source: Union catalogues
    Language: English
    Media type: Book
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    Other identifier:
    hdl: 10419/238096
    Series: Working paper series / Graduate Institute of International and Development Studies, International Economics Department ; no. HEIDWP2021, 05
    Subjects: BVAR; forecast evaluation; inflation forecasting
    Scope: 1 Online-Ressource (circa 38 Seiten), Illustrationen
  13. Nowcasting quarterly GDP growth during the COVID-19 crisis using a monthly activity indicator
    Author: Hartigan, Luke; Rosewall, Tom
    Published: July 2024
    Publisher:  Reserve Bank of Australia, [Sydney]

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    Series: Research discussion paper / Reserve Bank of Australia ; RDP 2024, 04
    Subjects: COVID-19; dynamic factor model; forecast evaluation; GDP growth; MIDAS regression; nowcasting; real-time data
    Scope: 1 Online-Ressource (circa 45 Seiten), Illustrationen
  14. Climate risks and prediction of sectoral REITs volatility
    international evidence
    Author: Salisu, Afees A.; Ogbonna, Ahamuefula Ephraim; Bouri, Elie; Gupta, Rangan
    Published: [2024]
    Publisher:  Department of Economics, University of Pretoria, Pretoria, South Africa

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    Series: Department of Economics working paper series / Department of Economics, University of Pretoria ; 2024, 34 (August 2024)
    Subjects: Climate risks; emerging and developed economies; sectoral REITs; realized volatility; feasible quasi-generalized least squares (FQGLS) method; forecast evaluation
    Scope: 1 Online-Ressource (circa 22 Seiten)
  15. Modeling and evaluating conditional quantile dynamics in VaR forecasts
    Author: Cipollini, Fabrizio; Gallo, Giampiero M.; Palandri, Alessandro
    Published: giugno 2023
    Publisher:  CRENoS, Cagliari, Italia

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    Language: English
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    Edition: Prima edizione
    Series: Working papers / CRENoS ; 2023, 08
    Subjects: Risk management; Value at Risk; dynamic quantile; asymmetric loss function; forecast evaluation
    Scope: 1 Online-Ressource (circa 42 Seiten), Illustrationen
  16. Three essays on volatility forecasting and forecast evaluation
    Author: Kleen, Onno
    Published: 2020
    Publisher:  Universitätsbibliothek Heidelberg, Heidelberg

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    Universitätsbibliothek Braunschweig
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    Bibliothek im Kurt-Schwitters-Forum
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    Universitätsbibliothek Heidelberg
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    ZBW - Leibniz-Informationszentrum Wirtschaft, Standort Kiel
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    Zentrale Hochschulbibliothek Lübeck
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    Leuphana Universität Lüneburg, Medien- und Informationszentrum, Universitätsbibliothek
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    UB Weimar
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    Source: Union catalogues
    Contributor: Conrad, Christian (AkademischeR BetreuerIn)
    Language: English
    Media type: Dissertation
    Format: Online
    Other identifier:
    Subjects: Economic forecasting; forecast evaluation; volatility; portfolio analysis; GARCH-MIDAS; low-volatility anomaly
    Scope: 1 Online-Ressource (iii, 157 Seiten), Diagramme
    Notes:

    Betreuer: Christian Conrad

    Freie Schlagwörter: Economic forecasting, forecast evaluation, volatility, portfolio analysis, GARCH-MIDAS, low-volatility anomaly

    Dissertation, Ruprecht-Karls-Universit ̈at Heidelberg, 2020
  17. Step by step - a quarterly evaluation of EU Commission's GDP forecasts
    Author: Heinisch, Katja
    Published: October 2024
    Publisher:  Halle Institute for Economic Research (IWH) - Member of the Leibniz Association, Halle (Saale), Germany

    The European Commission’s growth forecasts play a crucial role in shaping policies and provide a benchmark for many (national) forecasters. The annual forecasts are built on quarterly estimates, which do not receive much attention and are hardly... more

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    Universitäts- und Landesbibliothek Sachsen-Anhalt / Zentrale
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    ZBW - Leibniz-Informationszentrum Wirtschaft, Standort Kiel
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    The European Commission’s growth forecasts play a crucial role in shaping policies and provide a benchmark for many (national) forecasters. The annual forecasts are built on quarterly estimates, which do not receive much attention and are hardly known. Therefore, this paper provides a comprehensive analysis of multi-period ahead quarterly GDP growth forecasts for the European Union (EU), euro area, and several EU member states with respect to first-release and current-release data. Forecast revisions and forecast errors are analyzed, and the results show that the forecasts are not systematically biased. However, GDP forecasts for several member states tend to be overestimated at short-time horizons. Furthermore, the final forecast revision in the current quarter is generally downward biased for almost all countries. Overall, the differences in mean forecast errors are minor when using real-time data or pseudo-real-time data and these differences do not significantly impact the overall assessment of the forecasts’ quality. Additionally, the forecast performance varies across countries, with smaller countries and Central and Eastern European countries (CEECs) experiencing larger forecast errors. The paper provides evidence that there is still potential for improvement in forecasting techniques both for nowcasts but also forecasts up to eight quarters ahead. In the latter case, the performance of the mean forecast tends to be superior for many countries.

     
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    Source: Union catalogues
    Language: English
    Media type: Book
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    Other identifier:
    hdl: 10419/304456
    Series: IWH discussion papers ; 2024, no. 22 (October 2024)
    Subjects: consensus forecasts; data revision; forecast evaluation; forecast horizon; forecasting; nowcasting; professional forecasters
    Scope: 1 Online-Ressource (III, 22 Seiten, 0,87 MB), Diagramme
    Notes:

    Literaturverzeichnis: 19-22
  18. Rationalität und Qualität von Wirtschaftsprognosen
    Author: Scheier, Johannes
    Published: 2015
    Publisher:  Niedersächsische Staats- und Universitätsbibliothek Göttingen, Göttingen

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    Contributor: Bizer, Kilian (Akademischer Betreuer); Spiwoks, Markus (Akademischer Betreuer); Dierkes, Stefan (Akademischer Betreuer)
    Language: German
    Media type: Dissertation
    Format: Online
    Other identifier:
    hdl: 11858/00-1735-0000-0022-5FE8-0
    Subjects: Prognose; Wirtschaft; Experimentelle Wirtschaftsforschung; Qualität; Erwartungsbildung; Rationale Erwartung; Prognosefehler; Informationseffizienz; Wirtschaft; Prognose; Prognoseverfahren; Qualitätsmanagement; Konjunkturtest; Sachwert; Bewertung; Rationale Erwartung; Risiko; Spieltheorie; Experimentelle Wirtschaftsforschung
    Other subjects: (stw)Wirtschaftsprognose; (stw)Prognoseverfahren; (stw)Qualitätsmanagement; (stw)Frühindikator; (stw)Bewertung; (stw)Rationale Erwartung; (stw)Risiko; (stw)Spieltheorie; (stw)Experimentelle Ökonomik; volkswirtschaftliche Prognosen; Wirtschaftsprognosen; Konjunkturprognosen; Kapitalmarktprognose; Prognoseevaluation; Erwartungen; rationale Erwartungsbildung; Konsensprognosen; Informationseffizienz; Prognoserevisionen; Gegenwartsorientierte Verlaufsanpassung; Prognosegütemaße; Prognosequalität; Prognoseplanspiel; Unsicherheit; economic forecasting; business cycle forecasts; forecast quality; experimental planning game; information efficiency; consensus forecasts; early indicators; forecast evaluation; rational expectations; forecast rationality; expectations; forecast revisions; forecast measurement; uncertainty; Graue Literatur
    Scope: Online-Ressource
    Notes:

    Göttingen, Georg-August Universität, Diss., 2015
  19. Overfitting in judgment-based economic forecasts
    the case of IMF growth projections
    Author: Hellwig, Klaus-Peter
    Published: 2018
    Publisher:  International Monetary Fund, [Washington, D.C.]

    I regress real GDP growth rates on the IMF's growth forecasts and find that IMF forecasts behave similarly to those generated by overfitted models, placing too much weight on observable predictors and underestimating the forces of mean reversion. I... more

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    I regress real GDP growth rates on the IMF's growth forecasts and find that IMF forecasts behave similarly to those generated by overfitted models, placing too much weight on observable predictors and underestimating the forces of mean reversion. I identify several such variables that explain forecasts well but are not predictors of actual growth. I show that, at long horizons, IMF forecasts are little better than a forecasting rule that uses no information other than the historical global sample average growth rate (i.e., a constant). Given the large noise component in forecasts, particularly at longer horizons, the paper calls into question the usefulness of judgment-based medium and long-run forecasts for policy analysis, including for debt sustainability assessments, and points to statistical methods to improve forecast accuracy by taking into account the risk of overfitting

     
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  20. Germany's boom is maturing
    Author: Ademmer, Martin; Boysen-Hogrefe, Jens; Fiedler, Salomon; Groll, Dominik; Jannsen, Nils; Kooths, Stefan; Potjagailo, Galina
    Published: 2018
    Publisher:  [Kiel Institute for the World Economy], [Kiel]

    The economic upswing in Germany continues, although the expansion loses some steam. Compared to our summer forecast, we reduced our expectations for GDP growth by 0.1 and 0.3 percentage points in the current and next year, respectively, to 1.9... more

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    The economic upswing in Germany continues, although the expansion loses some steam. Compared to our summer forecast, we reduced our expectations for GDP growth by 0.1 and 0.3 percentage points in the current and next year, respectively, to 1.9 percent (2018) and 2.0 percent (2019). So for now, the boom in Germany persists. However, due to the already very high capacity utilization in many sectors, companies face increasing difficulties in continuing to expand their production at a brisk pace. This is especially palpable in the construction sector where in the face of very favorable circumstances production increases were quite restrained but prices rose markedly. The labor market also exhibits increasing shortages. Not least due to this, increases in employment should reduce over time. Next year, the expansionary fiscal policy will support the boom. The extensive tax reductions and spending increases will raise disposable incomes considerably, such that private consumption expenditures should grow by 2.2 percent —the fastest in 20 years. Because of the robust world economy after the phase of weakness at the beginning of the year, exports should also accelerate again. The additional temporary revenue of public authorities due to the current business cycle position is spent hand over fist on expenditures that are intended to persist in the long-run. The currently still sizeable structural budget surplus will therefore be eradicated by the year 2020.

     
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    Source: Union catalogues
    Language: English
    Media type: Book
    Format: Online
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    hdl: 10419/209505
    Series: Kiel Institute economic outlook ; Nr.47 (2018/Q3)
    Subjects: business cycle forecast; stabilization policy; leading indicators; outlook; forecast evaluation; investment income
    Scope: 1 Online-Ressource (36 Seiten), Illustrationen
  21. Constructing a new leading indicator for unemployment from a survey among German employment agencies
    Author: Hutter, Christian; Weber, Enzo
    Published: 2013
    Publisher:  IAB, Nürnberg

    The paper investigates the predictive power of a new survey implemented by the Federal Employment Agency (FEA) for forecasting German unemployment in the short run. Every month, the CEOs of the FEA’s regional agencies are asked about their... more

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    The paper investigates the predictive power of a new survey implemented by the Federal Employment Agency (FEA) for forecasting German unemployment in the short run. Every month, the CEOs of the FEA’s regional agencies are asked about their expectations of future labor market developments. We generate an aggregate unemployment leading indicator that exploits serial correlation in response behavior through identifying and adjusting temporarily unreliable predictions. We use out-of-sample tests suitable in nested model environments to compare forecasting performance of models including the new indicator to that of purely autoregressive benchmarks. For all investigated forecast horizons (1, 2, 3 and 6 months), test results show that models enhanced by the new leading indicator significantly outperform their benchmark counterparts. To compare our indicator to potential competitors we employ the model confidence set. Results reveal that models including the new indicator perform very well. Die vorliegende Arbeit untersucht eine neue Umfrage der Bundesagentur für Arbeit hinsichtlich ihres Potentials, kurzfristige Prognosen deutscher Arbeitslosenzahlen zu verbessern. In dieser Umfrage werden die Vorsitzenden der Geschäftsführung aller regionalen Agenturen monatlich zu ihren Arbeitsmarkterwartungen der nächsten drei Monate befragt. Wir bilden einen aggregierten Arbeitslosigkeitsfrühindikator und unterscheiden dabei auch zwischen temporär zuverlässigen und unzuverlässigen Agenturen, um serielle Korrelation im Antwortverhalten auszunutzen. Um die Prognosegüte des neuen Indikators mit der rein autoregressiver Benchmarkmodelle zu vergleichen, ziehen wir Out-of-Sample Evaluationstests heran, die für den Vergleich genesteter Modelle geeignet sind. Die Ergebnisse zeigen, dass Modelle mit dem neuen Frühindikator im Allgemeinen ihre rein autoregressiven Benchmarkmodelle schlagen, und zwar für alle untersuchten Prognosehorizonte (1, 2, 3 und 6 Monate). Desweiteren vergleichen wir unseren Frühindikator mit potenziellen Wettbewerbern und nutzen dafür das Model Confidence Set. Die Ergebnisse zeigen, dass Modelle mit dem neuen Frühindikator sehr gut abschneiden.

     
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    Source: Union catalogues
    Language: English
    Media type: Book
    Format: Online
    Other identifier:
    hdl: 10419/103070
    Series: IAB discussion paper ; 17/2013
    Subjects: survey data; forecast evaluation; nested models; model confidence set; unemployment
    Scope: Online-Ressource (30 S.), graph. Darst.
    Notes:

    Zsfassung in dt. Sprache
  22. Forecasting with a mismatch-enhanced labor market matching function
    Author: Hutter, Christian; Weber, Enzo
    Published: 2014
    Publisher:  IAB, Nürnberg

    This paper investigates the role of mismatch between job seekers and job openings for the forecasting performance of a labor market matching function. In theory, higher mismatch lowers matching efficiency which increases the risk that the vacancies... more

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    This paper investigates the role of mismatch between job seekers and job openings for the forecasting performance of a labor market matching function. In theory, higher mismatch lowers matching efficiency which increases the risk that the vacancies cannot be filled within the usual period of time. We investigate whether and to what extent forecasts of German job findings can be improved by a mismatch-enhanced labor market matching function. For this purpose, we construct so-called mismatch indicators that reflect regional, occupational and qualification-related mismatch on a monthly basis. In pseudo out-of-sample tests that account for the nested model environment, we find that forecasting models enhanced by the mismatch indicator significantly outperform their benchmark counterparts for all forecast horizons ranging between one month and a year. This is especially pronounced in the aftermath of the Great Recession where a low level of mismatch improved the possibility of unemployed to find a job again. Die Arbeit untersucht die Rolle von fehlender Passung (Mismatch) zwischen Arbeitslosen und offenen Stellen hinsichtlich der Prognosegüte der Matching-Funktion. Theoretisch sinkt die Matchingeffizienz mit höherem Mismatch, wodurch das Risiko steigt, dass die Vakanzen nicht innerhalb der normalen Zeit besetzt werden können. Wir untersuchen, ob und in welchem Umfang sich Vorhersagen von Abgängen aus Arbeitslosigkeit in Beschäftigung in Deutschland durch eine Matchingfunktion verbessern lassen, die die qualitative Passung von Angebot und Nachfrage berücksichtigt und somit über eine rein quantitative Betrachtung hinausgeht. Dazu konstruieren wir Mismatch-Indikatoren, die monatlich das Ausmaß von regionalen, beruflichen und qualifikatorischen Missverhältnissen zwischen Arbeitslosen und Vakanzen messen. Um die Prognosegüte dieses erweiterten Modells mit der des entsprechenden einfachen Stock-flow-Matchingmodells zu vergleichen, ziehen wir Out-of-Sample Evaluationstests heran, die für genestete Modelle geeignet sind. Die Ergebnisse zeigen, dass Modelle mit dem Mismatch-Indikator für alle untersuchten Prognosehorizonte (1 Monat bis 1 Jahr) signifikant besser abschneiden als die entsprechenden Benchmarkmodelle. Verbesserungspotenzial hinsichtlich der Prognosegüte zeigt sich vor allem für die Zeit nach der großen Finanz- und Wirtschaftskrise von 2008/2009, in der ein niedriges Mismatch-Level die Chancen für die Arbeitslosen erhöhte, wieder in Beschäftigung zu kommen.

     
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    Language: English
    Media type: Book
    Format: Online
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    hdl: 10419/103050
    Series: IAB discussion paper ; 16/2014
    Subjects: matching function; mismatch indicators; forecast evaluation
    Scope: Online-Ressource (28 S.), graph. Darst., Kt.
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    Zsfassung in dt. Sprache