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Competition and Innovation in Product Quality: Theory and Evidence from Eastern Europe and Central Asia

  • Fatma Nur Karaman EMAIL logo and Sajal Lahiri

Abstract

This paper examines how the degree of competition affects incentives to innovate in product quality in a symmetric Cournot oligopolistic model. We model product quality in a quality-ladder framework and find an inverted-U shaped relationship between the number of firms in an industry and R&D efforts in innovation. We test this theoretical prediction using firm-level data for Eastern European and Central Asian countries from the Business Environment and Enterprise Performance Survey and find strong support for it.

JEL Classification: O14; O25; O32; D22; D43

Appendix A

In this Appendix, we show how we derive the xi in eq. [8].

Rewrite first-order condition for x1 in steps as follows:

αβjinE(qj)xjci=2βxiE(qi2)E(qi)
αβj=1nE(qj)xjci=2βxiE(qi2)E(qi)βE(qi)xi
αβj=1nE(qj)xjci=xi2βE(qi2)E(qi)βE(qi)
[21]αβj=1nE(qj)xjci=E(qi)xiE(qi)2βE(qi2)E(qi)βE(qi)

Defining 2βE(qi2)/E(qi)βE(qi)=f(qi), we rewrite [21] as:

[22]E(qi)xi=αβj=1nE(qj)xjciE(qi)1f(qi).

Then summing over i, we get

[23]j=1nE(qj)xj=αβj=1nE(qj)xjcii=1nE(qi)f(qi)
[24]j=1nE(qj)xj1+βi=1nE(qi)f(qi)=[αci]i=1nE(qi)f(qi)
[25]j=1nE(qj)xj=[αci]i=1nE(qi)f(qi)1+βi=1nE(qi)f(qi)

Substituting for j=1nE(qj)xj in eq. [22], we get the expression for xi

[26]xi=[αci]E(qi)β2E(qi2)E(qi)211+i=1nE(qi)22E(qi2)E(qi)2

Appendix B: Proof of Proposition 1

We have already shown that effort on R&D (e) decreases with the number of firms n when n is large. We shall now examine the relationship between e and n for low values of n. In particular, when n=1, it can be shown from the expression of hn (eq. [19]) that hn|n=1 is positive if and only if 2E(q2)3E(q)2<0. That is, (de/dn)|n=1>0 if and only if 2E(q2)3E(q)2<0.

Using eq. [27], we find

[27]f(λ,ρ)=2E(q2)3E(q)2qˉ2=(2ρ3ρ2)λ26ρ(1ρ)λ+2(1ρ)3(1ρ)2.

From eq. [27], we get

[28]f(λ,ρ)|ρ=0=1<0,
[29]fρ=(λ1)2(λ2)6ρ(λ1),
[30]f(λ,ρ)|λ=0=1<0,
[31]fλ=2ρ(3+2λ)6ρ2(λ1).

From eq. [29], we find that f/ρ<0 if λ2. In this case, 2E(q2)3E(q)2 is negative for all values of ρ and therefore hn|n=1 is positive for all values of ρ. From eq. [31], we get f/λ<0 for all values of λ[1,1.5]. Putting all these together, we can say that hn|n=1 is positive if λ1.5, and therefore there is an inverted-U relationship between e and n if λ1.5.

Appendix C

Figure 3 Scatterplot of un1995 and sectorsh02
Figure 3

Scatterplot of un1995 and sectorsh02

Acknowledgments

We are extremely grateful to an anonymous referee for very helpful and constructive comments and suggestions.

References

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  1. 1

    European Commission, Investing in European Research, Science, Technology and Competitiveness Key Figures Report 2008/2009.

  2. 2

    An earlier paper by Swan (1970) assumes a similar demand function where consumers demand total durability of light bulbs.

  3. 3

    As in Tishler and Milstein (2009), all decisions are made ex ante.

  4. 4

    See Appendix A for the steps.

  5. 5

    The term xi/ei is missing in eq. [10] because of the envelope property.

  6. 6

    The parameter λ being less that 1.5 is a sufficient condition, and the result will hold even when λ is somewhat larger than the value 1.5.

  7. 7

    World Bank also provides data for 2005, 2009, and a panel data for 3 years. For these years, R&D intensity variable for some sectors and countries have no or very few observations. Specifically 4,548 out of 5,367 firms report zero R&D intensity in 2005, and we have only 967 observations for this variable out of 11,668 firms in 2009. In addition, one of our competition measures, exact number of competitors, is not included in either 2009 or panel questionnaire.

  8. 8

    Correlation between un1995 and sectorsh02 is high: 0.30 for the full sample. However there does not seem to be a systematic relationship between the two. See Appendix 4.

  9. 9

    Other control variables suggested by the literature (see, for example, Correa, Fernandes, and Uregian (2010), Gorodnichenko and Schnitzer (2010) and Ayyagari, Demirguc-Kunt, and Maksimovic (2007)) include firm age, cost of financing, share of skilled labor force, and capacity utilization. We do not find an evidence of a significant effect of these variables, thus those results are not reported here. We also computed a firm-level inefficiency variable since it is believed to be an important determinant of R&D absorption (see, for example, Kravtsova and Radosevic (2012)). The variable’s correlations with our competition measures are over 0.30. Controlling for inefficiency, we find evidence of the expected relationship between competition and innovation, however, we believe the high correlation may bias the results thus they are not reported here to save space.

  10. 10

    The EU countries include Czech Republic, Estonia, Hungary, Latvia, Lithuania, Poland, Slovak Republic, and Slovenia.

  11. 11

    The 2002 report includes only 14 countries of our sample.

  12. 12

    We have compared the responses to both questions. They do not match for the majority of the firms.

  13. 13

    The procedure is the well-known control function approach.

  14. 14

    Stata also calculates a Smith-Blundell test statistic which is distributed as F(m,nk), where m is the number of explanatory variables specified as endogenous in the model and n is the number of observations. Since we use a quadratic form, m=2 for our model. A rejection indicates that the standard Tobit estimator should not be employed. The associated test statistic for the full sample with instrument impsh is 0.2338 and the p-value is 0.7915. For the instrument regul, Smith-Blundell test statistic is 1.316 and the p-value is 0.2685. Therefore, we can again claim that the estimated Tobit form in eq. [20] with ncomp exogenous is the correct model.

Published Online: 2014-6-28
Published in Print: 2014-7-1

©2014 by Walter de Gruyter Berlin / Boston

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