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The effect of uncertainty on UK investment authorisation: Homogenous vs. heterogeneous estimators

Author

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  • Ciaran Driver
  • Katsushi Imai
  • Paul Temple
  • Giovanni Urga

Abstract

This paper compares pooled and non-pooled models of UK capital investment using the Confederation of British Industry’s (CBI) Industrial Trends Survey, focusing on the impact of uncertainty. The uncertainty measure is based on the cross sectional dispersion of optimism about the future business conditions in the industry in which the firm operates. The panel data estimation shows that uncertainty has quantitatively important negative effects on investment. However, if we look at the estimation results at the industry level, we find a great diversity in both estimated elasticities and t-statistics, providing valuable information not available from the pooled model. Finally, we compare the forecast performances of the above models; this analysis confirms that pooled estimators are generally better than non-pooled estimators in terms of out-of-sample forecast performance, but the difference between the two is not very large. Copyright Springer-Verlag 2004

Suggested Citation

  • Ciaran Driver & Katsushi Imai & Paul Temple & Giovanni Urga, 2004. "The effect of uncertainty on UK investment authorisation: Homogenous vs. heterogeneous estimators," Empirical Economics, Springer, vol. 29(1), pages 115-128, January.
    • Handle: RePEc:spr:empeco:v:29:y:2004:i:1:p:115-128
    DOI: 10.1007/s00181-003-0192-2
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    Cited by:

    1. Salisu, Afees A. & Vo, Xuan Vinh, 2021. "Firm-specific news and the predictability of Consumer stocks in Vietnam," Finance Research Letters, Elsevier, vol. 41(C).
    2. Aytekin GÜVEN & Arzu AKKOYUNLU-WIGLEY, 2018. "The Effects of Market Structure on Uncertainty-Investment Relationship: Evidence from Turkish Manufacturing Industry," Sosyoekonomi Journal, Sosyoekonomi Society, issue 26(37).
    3. Catherine Fuss & Philip Vermeulen, 2008. "Firms' investment decisions in response to demand and price uncertainty," Applied Economics, Taylor & Francis Journals, vol. 40(18), pages 2337-2351.
    4. Badi H. Baltagi, 2008. "Forecasting with panel data," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(2), pages 153-173.
    5. Baltagi, Badi H., 2013. "Panel Data Forecasting," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 995-1024, Elsevier.
    6. Binding, Garret & Dibiasi, Andreas, 2017. "Exchange rate uncertainty and firm investment plans evidence from Swiss survey data," Journal of Macroeconomics, Elsevier, vol. 51(C), pages 1-27.
    7. Kang, Wensheng & Lee, Kiseok & Ratti, Ronald A., 2014. "Economic policy uncertainty and firm-level investment," Journal of Macroeconomics, Elsevier, vol. 39(PA), pages 42-53.
    8. Badi H. Baltagi, 2021. "Dynamic Panel Data Models," Springer Texts in Business and Economics, in: Econometric Analysis of Panel Data, edition 6, chapter 0, pages 187-228, Springer.
    9. Trinks, Arjan & Mulder, Machiel & Scholtens, Bert, 2022. "External carbon costs and internal carbon pricing," Renewable and Sustainable Energy Reviews, Elsevier, vol. 168(C).
    10. Driver, Ciaran & Temple, Paul & Urga, Giovanni, 2008. "Real options -- delay vs. pre-emption: Do industrial characteristics matter?," International Journal of Industrial Organization, Elsevier, vol. 26(2), pages 532-545, March.
    11. Bettina Becker & Stephen Hall, 2013. "Do R&D strategies in high-tech sectors differ from those in low-tech sectors? An alternative approach to testing the pooling assumption," Economic Change and Restructuring, Springer, vol. 46(2), pages 183-202, May.
    12. Afees A. Salisu & Elias A. Udeaja & Silva Opuala-Charles, 2022. "Central Bank Independence And Price Stability Under Alternative Political Regimes: A Global Evidence," Bulletin of Monetary Economics and Banking, Bank Indonesia, vol. 25(2), pages 155-172, August.
    13. Ciaran Driver & Paul Temple & Giovanni Urga, 2005. "Explaining the Diversity of Industry Investment Responses to Uncertainty Using Long Run Panel Survey Data," School of Economics Discussion Papers 0405, School of Economics, University of Surrey.
    14. Andrey V. Polbin & Andrey V. Shumilov, 2022. "Forecasting Output Growth of Russian Manufacturing Industries Using Panel Data Models [Об Использовании Моделей Панельных Данных Для Прогнозирования Темпов Роста Отраслей Российской Обрабатывающей ," Russian Economic Development, Gaidar Institute for Economic Policy, issue 2, pages 15-19, February.
    15. Marina Riem, 2016. "Corporate investment decisions under political uncertainty," ifo Working Paper Series 221, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    16. Salisu, Afees A. & Vo, Xuan Vinh, 2020. "Predicting stock returns in the presence of COVID-19 pandemic: The role of health news," International Review of Financial Analysis, Elsevier, vol. 71(C).
    17. Andrey V. Polbin & Andrey V. Shumilov, 2022. "Об Использовании Моделей Панельных Данных Для Прогнозирования Темпов Роста Отраслей Российской Обрабатывающей Промышленности," Russian Economic Development (in Russian), Gaidar Institute for Economic Policy, issue 2, pages 15-19, February.

    More about this item

    Keywords

    Investment; uncertainty; panel data estimation; E22; C23;
    All these keywords.

    JEL classification:

    • E22 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Investment; Capital; Intangible Capital; Capacity
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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