Skip to main content

Advertisement

SpringerLink
Log in

How do firms use innovations to hedge against economic and political uncertainty? Evidence from a large sample of nations

  • Published:
The Journal of Technology Transfer Aims and scope Submit manuscript

Abstract

Using data on 135 countries, this paper studies the determinants of process innovation introduction, focusing on the impacts of economic and political uncertainties. Greater uncertainty, on the one hand, can lower potential benefits from innovation introductions, while on the other hand, the introduction of innovations might enable firms to hedge against uncertainty. The empirical literature has mostly considered uncertainty-investment nexus, and this study uniquely considers uncertainty-innovation introductions. Employing two different measures of economic and political uncertainty across different time lags, results are consistent with the hedging story—greater economic and political uncertainties induce firms to introduce process innovations to the market. With regard to firms’ attributes, sole proprietorships and R&D-performing firms were more likely to introduce innovations, while firms located in island nations were less likely to do so. Firms’ size and vintage did not have an appreciable influence on the incentives to introduce innovations. Some policy implications of these findings are discussed.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1

Similar content being viewed by others

Notes

  1. Since they are two sides of the same coin, we use the terms stability and uncertainty in reference to the same phenomenon.

  2. A recent focus of the uncertainty-investment literature has been in the context of the Great Recession, especially with regard to the euro-zone nations (Caldara et al. 2016; Meinen and Roehe 2017).

  3. While technical uncertainty is related to the supply of innovations (i.e., whether firms will actually succeed in coming up with an invention), the economic and political uncertainties we consider are related to the payoffs from market introductions—i.e., whether costs of innovation introduction and its diffusion and/or demand for the innovation are going to be affected by economic and political upheavals.

  4. As discussed above, our consideration of economic and political uncertainties does not exhaust all uncertainties that might potentially impact the research process (Goel 1995, 2007; Kamien and Schwartz 1982; Reinganum 1989).

    More broadly, Milliken (1987) makes the distinction between state, effect, and response uncertainties. Following this characterization, our work can be seen as considering state uncertainties in the form of economic and political uncertainties.

  5. Baker et al. (2015) consider policy uncertainty that has political and economic components.

  6. Our economic uncertainty measurement follows the related literature through the use of standard deviations or variances of relevant variables (Czarnitzki and Toole 2011; Goel and Ram 1999, 2001; Pindyck and Solimano 1993). On the other hand, the political uncertainty measures are based on indices that include variability or uncertainty (see Table 1 for details).

  7. Inflation uncertainty has been considered in other contexts by various scholars, see, for example, Bhar and Mallik (2013) and Berument et al. (2011).

  8. The index is constructed from several sources, including the Economist Intelligence Unit, the World Economic Forum, and the Political Risk Services. http://info.worldbank.org/governance/wgi/pdf/WGI.pdf.

  9. http://www.systemicpeace.org/inscr/SFImatrix2016c.pdf.

  10. Firms’ scale might be tied to the variable Q (output) in the basic theoretical model sketched in Sect. 2. Further, sole proprietorship can be viewed as capturing a dimension of market structure. The nexus between market structure and innovation has intrigued economists since the time of Schumpeter; see, for more recent examples, Kamien and Schwartz (1982) and Pohlmeier (1992).

  11. For a comparison of the Enterprise Survey dataset with the complementary Doing Business survey, also produced through the World Bank, see http://www.enterprisesurveys.org/Methodology/Enterprise-Surveys-versus-Doing-Business.

  12. http://www.enterprisesurveys.org/methodology.

  13. A few countries had surveys for multiple years (see the “Appendix” for details). We decided to use all available information in our analysis. Individual country sample sizes for any given year ranged from 1200 to 1800 interviews for large economies to 360 interviews in medium-sized economies, and for smaller economies, 150 interviews.

  14. Estimation is carried out using the STATA command fracreg. A beta distribution is inappropriate as there are cases in the dataset of endpoint values of the [0, 1] interval.

  15. Columns 4 and 7, respectively, in Table 2.

  16. Our available R&D variable is the percentage of firms in a country that spend on research and development (Table 1). Another pertinent variable would be the amount of R&D spending—unfortunately, we do not have corresponding information for countries/years included in the analysis.

  17. Interestingly, in all four cases presented in Fig. 1 the relationships between the uncertainty measure and conditional means are nearly linear.

  18. Additional details are available upon request.

  19. In our micro sample of nearly 64,000 observations, the mean of the political instability variable was 0.63.

  20. Unfortunately, we could find no corresponding question in the ES survey on business manager perceptions of economic uncertainty.

  21. An exception is that there is stronger evidence that firm size contributes positively to innovation over what was observed before.

  22. To conserve space, we report values for the uncertainty indicators over the previous 3 years.

  23. The underlying data for legal origin were from Treisman (2007).

  24. Another possible explanation might lie in the distinction between “good” and “bad” (economic) uncertainty, as noted in a different context by Segal et al. (2015). Such an exercise, involving construction of corresponding indices of political uncertainty, is beyond the scope of present work.

References

  • An, H., Chen, Y., Luo, D., & Zhang, T. (2016). Political uncertainty and corporate investment: Evidence from China. Journal of Corporate Finance, 36(C), 174–189.

    Article  Google Scholar 

  • Arrow, K. J. (1971). Essays in the theory of risk-bearing. Amsterdam: North-Holland.

    Google Scholar 

  • Baker, S. R., Bloom, N., & Davis, S. J. (2015). Measuring economic policy uncertainty. National Bureau of Economic Research, working paper #21633, October.

  • Berument, M. H., Yalcin, Y., & Yildirim, J. O. (2011). The inflation and inflation uncertainty relationship for Turkey: A dynamic framework. Empirical Economics, 41(2), 293–309.

    Article  Google Scholar 

  • Bhar, R., & Mallik, G. (2013). Inflation uncertainty, growth uncertainty, oil prices, and output growth in the UK. Empirical Economics, 45(3), 1333–1350.

    Article  Google Scholar 

  • Binding, G., & Dibiasi, A. (2017). Exchange rate uncertainty and firm investment plans evidence from Swiss survey data. Journal of Macroeconomics, 51(C), 1–27.

    Article  Google Scholar 

  • Bloom, N. (2007). Uncertainty and the dynamics of R&D. American Economic Review, 97(2), 250–255.

    Article  Google Scholar 

  • Bontempi, M. E. (2016). Investment-uncertainty relationship: Differences between intangible and physical capital. Economics of Innovation and New Technology, 25(3), 240–268.

    Article  Google Scholar 

  • Caldara, D., Fuentes-Albero, C., Gilchrist, S., & Zakrajšek, E. (2016). The macroeconomic impact of financial and uncertainty shocks. European Economic Review, 88, 185–207.

    Article  Google Scholar 

  • Clemens, J., & Veuger, S. (2017). Risks to the returns to medical innovation: The case of myriad genetics. Contemporary Economic Policy, 35(2), 345–357.

    Article  Google Scholar 

  • Czarnitzki, D., & Toole, A. A. (2011). Patent protection, market uncertainty, and R&D investment. Review of Economics and Statistics, 93(1), 147–159.

    Article  Google Scholar 

  • Darby, J., Hallett, A. H., Ireland, J., & Piscitelli, L. (1999). The impact of exchange rate uncertainty on the level of investment. Economic Journal, 109(454), 55–67.

    Article  Google Scholar 

  • Dasgupta, P., & Stiglitz, J. (1980). Industrial structure and the nature of innovative activity. Economic Journal, 90(358), 266–293.

    Article  Google Scholar 

  • Dixit, A. K., & Pindyck, R. S. (1994). Investment under uncertainty. Princeton, NJ: Princeton University Press.

    Book  Google Scholar 

  • Eraker, B., Johannes, M., & Polson, N. (2003). The impact of jumps in volatility and returns. Journal of Finance, 58(3), 1269–1300.

    Article  Google Scholar 

  • Goel, R. K. (1990). Innovation, market structure, and welfare: A Stackelberg model. The Quarterly Review of Economics and Business, 30(1), 40–53.

    Google Scholar 

  • Goel, R. K. (1995). Spillovers, rivalry and R&D investment. Southern Economic Journal, 62(1), 71–76.

    Article  Google Scholar 

  • Goel, R. K. (2007). Research spending under regulatory uncertainty. Journal of Technology Transfer, 32(6), 593–604.

    Article  Google Scholar 

  • Goel, R. K., & Göktepe-Hultén, D. (2019). Risk attitudes, patenting and invention disclosures by academic researchers. Journal of Technology Transfer, 44(1), 155–166.

    Article  Google Scholar 

  • Goel, R. K., & Nelson, M. A. (2018). Determinants of process innovation introductions: Evidence from 115 developing countries. Managerial and Decision Economics, 39(5), 515–525.

    Article  Google Scholar 

  • Goel, R. K., & Ram, R. (1999). Variations in the effect of uncertainty on different types of investment: An empirical investigation. Australian Economic Papers, 38(4), 481–492.

    Article  Google Scholar 

  • Goel, R. K., & Ram, R. (2001). Irreversibility of R&D investment and the adverse effect of uncertainty: Evidence from the OECD countries. Economics Letters, 71(2), 287–291.

    Article  Google Scholar 

  • Ivus, O., & Wajda, J., (2018). Fluctuations in uncertainty and R&D investment. CIGi papers no. 175, June 2018.

  • Jens, C. E. (2017). Political uncertainty and investment: Causal evidence from U.S. gubernatorial elections. Journal of Financial Economics, 124(1), 563–579.

    Article  Google Scholar 

  • Kamien, M. I., & Schwartz, N. L. (1980). A generalized hazard rate. Economics Letters, 5(3), 245–249.

    Article  Google Scholar 

  • Kamien, M. I., & Schwartz, N. L. (1982). Market Structure and Innovation. Cambridge: Cambridge University Press.

    Google Scholar 

  • Kang, W., Lee, K., & Ratti, R. A. (2014). Economic policy uncertainty and firm-level investment. Journal of Macroeconomics, 39(A), 42–53.

    Article  Google Scholar 

  • Koenker, R., & Hallock, K. F. (2001). Quantile regression. Journal of Economic Perspectives, 15(4), 143–156.

    Article  Google Scholar 

  • Loury, G. C. (1979). Market structure and innovation. Quarterly Journal of Economics, 93(3), 395–410.

    Article  Google Scholar 

  • Meinen, P., & Roehe, O. (2017). On measuring uncertainty and its impact on investment: Cross-country evidence from the euro area. European Economic Review, 92(C), 161–179.

    Article  Google Scholar 

  • Milliken, F. J. (1987). Three types of perceived uncertainty about the environment: State, effect, and response uncertainty. Academy of Management Review, 12(1), 133–143.

    Article  Google Scholar 

  • Morikawa, M. (2016). Business uncertainty and investment: Evidence from Japanese companies. Journal of Macroeconomics, 49(C), 224–236.

    Article  Google Scholar 

  • Papke, L. E., & Wooldridge, J. M. (1996). Econometric methods for fractional response variables with an application to 401(k) plan participation rates. Journal of Applied Econometrics, 11(6), 619–632.

    Article  Google Scholar 

  • Pindyck, R. S. (1991). Irreversibility, uncertainty, and investment. Journal of Economic Literature, 29(3), 1110–1148.

    Google Scholar 

  • Pindyck, R. S., & Solimano, A. (1993). Economic instability and aggregate investment, (including comments and discussion). In O. J. Blanchard & S. Fischer (Eds.), NBER macroeconomics annual 1993 (Vol. 8, pp. 259–318). Cambridge, MA: MIT Press.

    Google Scholar 

  • Pohlmeier, W. (1992). On the simultaneity of innovations and market structure. Empirical Economics, 17(2), 253–272.

    Article  Google Scholar 

  • Reinganum, J. F. (1989). The timing of innovation: research, development, and diffusion. In R. Schmalensee & R. D. Willig (Eds.), Handbook of industrial organization (Vol. I, pp. 849–908). Amsterdam: North-Holland.

    Google Scholar 

  • Segal, G., Shaliastovich, I., & Yaron, A. (2015). Good and bad uncertainty: Macroeconomic and financial market implications. Journal of Financial Economics, 117(2), 369–397.

    Article  Google Scholar 

  • Stokey, N. L. (2016). Wait-and-see: Investment options under policy uncertainty. Review of Economic Dynamics, 21, 246–265.

    Article  Google Scholar 

  • Tandon, P. (1984). Innovation, market structure, and welfare. American Economic Review, 74(3), 394–403.

    Google Scholar 

  • Tenreyro, S. (2007). On the trade impact of nominal exchange rate volatility. Journal of Development Economics, 82(2), 485–508.

    Article  Google Scholar 

  • Treisman, D. (2007). What have we learned about the causes of corruption from ten years of cross-national empirical research? Annual Review of Political Science, 10, 211–244.

    Article  Google Scholar 

  • Wooldridge, J. M. (2010). Econometric analysis of cross section and panel data (2nd ed.). Cambridge, MA: MIT Press.

    Google Scholar 

Download references

Acknowledgements

An earlier version of this paper was circulated as a Kiel Working Paper (#2142). Goel thanks the Katie School of Insurance for support. Comments from presentation participants at Fukuyama University, Okayama University, Western Economic Association International and Western Risk and Insurance Association are appreciated.

Author information

Authors and Affiliations

  1. Department of Economics, Illinois State University, Normal, IL, 61790-4200, USA

    Rajeev K. Goel

  2. Kiel Institute for the World Economy, Kiel, Germany

    Rajeev K. Goel

  3. University of Akron, Akron, USA

    Michael A. Nelson

Authors
  1. Rajeev K. Goel
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Michael A. Nelson
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Rajeev K. Goel.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Appendix

Appendix

1.1 Countries included in the data set

Afghanistan (2014), Albania (2013), Antigua and Barbuda (2010), Argentina (2006, 2010), Armenia (2013), Azerbaijan (2013), Bahamas (2010), Bangladesh (2013), Barbados (2010), Belarus (2013), Belize (2010), Benin (2016), Bhutan (2015), Bolivia (2006, 2010), Bosnia and Herzegovina (2013), Bulgaria (2013), Burundi (2014), Cambodia (2013, 2016), Cameroon (2016), Central African Republic (2011), Chile (2006, 2010), China (2012), Colombia (2006, 2010), Congo, Dem. Rep. (2013), Costa Rica (2010), Côte d’Ivoire (2016), Croatia (2013), Czech Republic (2013), Djibouti (2013), Dominica (2010), Dominican Republic (2010, 2016), Ecuador (2006, 2010), Egypt, Arab Rep. (2013), El Salvador (2006, 2010, 2016), Estonia (2013), Ethiopia (2011, 2015), Georgia (2013), Ghana (2013), Grenada (2010), Guatemala (2006, 2010), Guinea (2016), Guyana (2010), Honduras (2006, 2010), Hungary (2013), India (2014), Indonesia (2015), Israel (2013), Jamaica (2010), Jordan (2013), Kazakhstan (2013), Kenya (2013), Kosovo (2013), Kyrgyz Republic (2013), Laos PDR (2016), Latvia (2013), Lebanon (2013), Lesotho (2016), Lithuania (2013), Macedonia, FYR (2013), Malawi (2014), Malaysia (2015), Mali (2016), Mauritania (2014), Mexico (2006, 2010), Moldova (2013), Mongolia (2013), Montenegro (2013), Morocco (2013), Myanmar (2014, 2016), Namibia (2014), Nepal (2013), Nicaragua (2006, 2010), Nigeria (2014), Pakistan (2013), Panama (2006, 2010), Papua New Guinea (2015), Paraguay (2006, 2010), Peru (2006, 2010), Philippines (2015), Poland (2013), Romania (2013), Russian Federation (2012), Rwanda (2011), Senegal (2014), Serbia (2013), Slovak Republic (2013), Slovenia (2013), Solomon Islands (2015), South Sudan (2014), Sri Lanka (2011), St. Kitts and Nevis (2010), St. Lucia (2010), St. Vincent and the Grenadines (2010), Sudan (2014), Suriname (2010), Swaziland (2016), Sweden (2014), Tajikistan (2013), Tanzania (2013), Thailand (2016), Timor-Leste (2015), Togo (2016), Trinidad and Tobago (2010), Tunisia (2013), Turkey (2013), Uganda (2013), Ukraine (2013), Uruguay (2006, 2010), Uzbekistan (2013), Venezuela, R.B. (2010), Vietnam (2015), West Bank and Gaza (2013), Yemen (2013), Zambia (2013), Zimbabwe (2011, 2016)

  1. The year of survey(s) is in parentheses

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Goel, R.K., Nelson, M.A. How do firms use innovations to hedge against economic and political uncertainty? Evidence from a large sample of nations. J Technol Transf 46, 407–430 (2021). https://doi.org/10.1007/s10961-019-09773-6

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10961-019-09773-6

Keywords

JEL Classification

Search

Navigation