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Macroeconomics And Innovation Druid Summer 14 June
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Macroeconomics And Innovation Druid Summer 14 June



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  • Introduction: I would like to first thank you for attending my presentation. This is my first presentation of this research, so please do not hesitate to interrupt and ask questions. Name From? New Mexico in the States. What doing now? I am currently a PhD student in the innovation and environmental sciences department.
  • I asked myself whether we knew SMEs could benefit from cyclical downturns, and recessions, by innovating. I am to investigate some typical macro-economic variable effect on innovations in SME in the Netherlands. (Go over results)
  • Schumpeter 1934 and Schmookler 1966 created the terminology of supply push and pull of technology innovations in an economy. While we accept that were technological opportunities, knowledge resources, etc, are present, innovations do rather well, but this is far from the whole story as Geroski and Gregg would say. Schumpeter creative destruction from new and small firms. Schmookler says that demand is important, but not just demand but changing competition structures that firms are influenced by is important. To illustrate this, Mowery and Rosenberg in 1979 say we should demonstrate that demand conditions change over time. So far very little research on changing demand structures has been done with SME innovation research. Heger (2004) asked whether the decision to innovate in SME manufacturing firms was pro- or counter-cyclical but finds various evidence of both. Koellinger & Thurik (2009) research the business startup rates during the business cycle and find that typically, new firms are created more before a recession is over and only wane well before a recession occurs. Importantly, we can say demand can have either pro- or counter- or no effect. But what are the mechanisms behind the ‘demand’ effect? We now will illustrate the possible effects of the macro-economy on the business cycle.
  • First I look into the general effects on SME innovation from GDP growth. Why GDP growth? Because it is a catch-all measurement of value added for a national economy. It represents the growth or lack of growth in a simple figure that has the longest reaching capabilities. Second I look into different components of macro-economy on innovation. Why others? Because GDP is a catch-all it may mask some of the effects from different markets such as labor, financial, etc. Need to test these mechanisms as well. Why not others? From theory we know demand influences innovation but do not know the timing here. The most reasonable and feasible measureable variables are consumption, unemployment and interest rates.
  • Innovation as luxury Geroski and Gregg (1997) Limited ability of markets to absorb new products and services. Consumer spending power. Limited window of opportunity for innovations to be introduced successfully before imitators. Expectation of SME managers on future consumer preference and power, moves pro-cyclically with macro-economy. Recession lowers power and scope, so managers choose to launch innovations when economy recovers. For process innovations, more growth prospects urge more investments into new efficiency gains and processes. Opportunity for business expansion creates opportunity for new processes. Pitstop – One sum operation; opportunity cost as innovation becomes less costly, more innovation during recession. Strategic process – highly innovative firms will choose to innovate constantly, despite the macroeconomic conditions. The timeframe may be longer than the cycle. Sunk costs into innovative projects.
  • Repeat innovation as luxury and opportunity to invest. Access to labor – Product - employees matter, especially for SMEs. labor market becomes more competitive, attract new employees. Process - innovations, the need to gain efficiency when you are unable to attract new employees becomes crucial to survival. We expect then that as the labor market competitiveness increases, the macro-economy slows, the need for efficiency gains increases; hence a counter-cyclical attachment as labor becomes cheaper Constrained Financing: relatively small balance sheets and riskiness increases interest rates that banks or financier ask of them. However, this may not be true for crisis and recession;
  • Pooled cross-section approach excludes longitudinal study. Response rates of 50 – 60%. Read slide
  • The definitions of product innovations are radical, or new to the industry, not imitation because they only follow new introductions. We use logistic regressions because of the binary response variable. Importantly, we correct for timeframe of the dependent variable by averaging the macroeconomic indicator over the past three years. We tried lags but have no evidence of anything. It certainly seems possible that when asked about the innovation activity over the past three years then answers are averaged, hence, the effects of the business cycle will be averaged.
  • Here we control for some typical SME innovation characteristics like the use of universities, research centers, outside people etc. Also, between firms their may be some formal or informal contracts to assist in innovations. Strategic partnerships etc. Measure innovation intensity we controlled for the number of employees dedicated to innovation. An important control here is the size. This likely captures many aspects of innovativeness for SMEs that are not included in the survey. For example financing, resources, business structure, culture etc. Because the effect of firm size is not linear, one additional employee means more for a very small operation than to a larger company, we transformed natural log. Survival bias on the one hand innovative firms are more likely to survive because they have better capabilities, on the other hand innovative firms reveal more risky behavior and are thus more likely to fail => since we do not know the net result of these two mechanisms, we cannot say much sensible about the effect of the survival bias on the (mis) interpretation of our cross-sectional results.
  • Looking at the macroeconomic indicators: 2000 to 2002 – stagnation and economic decline of 4.4% with unemployment as high as 6.3% due to slowing trade, the burst, and the September 11 th attacks. 2008-2009 growth drops to -4.9% and unemployment up to 5%. Extremely low interest rates and steep decline unlike 2000 -2002.
  • Closely related to the real GDP of the economy.
  • Steady decrease from 5.42% to 3.37%; economic growth from 2006 to 2007 but rates lowered in 2009.
  • At first glance, in 2006 the year of highest growth the most innovations. In 2002, 2008, and 2009 the lowest. High percentage but decreasing process innovations. Interestingly, both show upswing during last year.
  • Logistic Regression Analysis for product innovations at the aggregate-level Note the pro-cyclical for GDP, positive effects; evidence of strategic innovation for man/trade.
  • With components there is positive for DC and UN supporting the luxury and access to employs. Negative means that the financing conditions have negative effect.
  • Product and service innovations are pro-cyclical; innovation as a strategic process No evidence of strategic process for highly innovative service firms. Opportunity to invest as economy is growing. For example, buying a new computer is more likely when economy is growing.
  • Innovation as Luxury (although not a aggregate but in quartiles); Evidence of more access to skilled labor, evidence that interest rates do indicate innovations. Process; opportunity to invest and cheap labor replacing process over the cycle. This ultimately means that when we say “demand matters” its what competition structure that you are talking about for what innovation; Schmookler. This does not support the general thesis that SMEs are bringing new innovations more during recessions, generally, but may agree when only highly innovative industries are included.
  • Again, thank you for the opportunity to discuss this research and please, if you have any questions and comments.


  • 1. Macroeconomic Dynamics and Innovation; SME product innovation over the business cycle Neil Thompson Erik Stam
  • 2. Overview
    • Question: To what extent and how do macroeconomic dynamics effect product innovations?
    • Aim: is to explicate the mechanisms in which the macro-economy may have an affect on product innovations from small and medium sized businesses (SMEs) from 1999-2009.
    • Macroeconomic indicators: real GDP growth, labor market, consumer demand, financial market dynamics.
    • Results: Evidence of Innovation as luxury good effect and a labor market effect on product innovations. Evidence of innovation as a strategic process for highly innovative industries.
  • 3. Schumpeter and Schmookler
    • Supply push of technology (Schumpeter)
    • Demand pull of needs for innovation (Schmookler)
    • Mowery and Rosenberg’s (1979) request to demonstrate demand conditions that are changing.
  • 4. Categories of Hypotheses
    • I – The effect of macroeconomic dynamics in general, measured by dynamics in GDP growth.
    • II – The effect of components of macroeconomic dynamics, namely domestic consumption, unemployment, and interest rates.
  • 5. Category I - Hypotheses
    • I 1. There is a pro-cyclical ( positive ) effects of GDP on product innovation
    • [ Innovation as Luxury ]
    • [Incentive to Invest]
    • I 2. There is a counter-cyclical ( negative ) effect of GDP on product innovation
    • [ Pit-stop theory of Recession ] (Aghion et al. 1993)
    • I 3. Product innovation of firms in the most innovative industries are insensitive to GDP dynamics.
    • [ Strategic Innovation theory ].
  • 6. Category II - Hypotheses
    • II.1 There is a positive relation of domestic consumption with (product) innovation.
    • [ Innovation as Luxury , specified as consumption effect] Schmookler (1966); [ Incentive to Invest]
    • II.2 There is a positive relation of unemployment with product innovation.
    • [ Access to Skilled Labor ] (Heger 2004)
    • II.3 There is a negative relation of interest rate with product innovation
    • [ Constrained Finance ] (Geroski and Gregg 1997)
  • 7. Data and Methods
    • EIM dataset from 1999-2009 (excluding 2001); innovation questionnaire.
    • Average 3,383 respondents; 7,593 the most in 2006 and 1,612 the least in 2000.
    • 16 sectors of the Dutch economy.
    • Macroeconomic indicators are from Centraal Bureau voor de Statistiek (CBS) in the Netherlands.
  • 8. Data and Methods cont’d
    • Product innovation = new product or service new to the industry.
    • Logistic regressions; “has your firm innovated a product or services new to the industry over the past three years?”
    • “ Has your firm introduced new methods or processes of production over the past three years?”
    • Average of yearly macroeconomic variables over three years to correct for timeframe.
  • 9. Data and Methods cont’d
    • Control and innovation statistics
    • Use of external networks (Freel 2000, 2003)
    • Inter-firm cooperation (Brouwer and Kleinknecht 1996)
    • Employees dedicated towards innovation (Sundbo 1996)
    • Size classes
    • Sectors
    • Limitation: Possible survival bias
  • 10. Real GDP growth and unemployment dynamics
    • 2000 to 2002 recession
    • 2008 through 2009 recession
  • 11. Domestic consumption rates
    • Domestic consumption similar to real GDP growth
  • 12. Long term interest rates
    • Decreasing rates from 2000 to 2006.
  • 13. Product and process innovations
    • Steady decrease in process innovations
    • Radical product innovations average at 23%.
  • 14. Innovation Inputs
    • Relatively stable use of external resources and inter-firm cooperation.
  • 15. Empirical Results
  • 16. Category I – Product Innovations and macroeconomic dynamics using GDP VARIABLES Aggregate Most Innovative Manufacturing/Trade Most Innovative Service Rest of Population   marginal effects marginal effects marginal effects marginal effects Real GDP 0.009*** 0.005 0.013*** 0.012*** Assistance from External Networks 0.055*** 0.072*** 0.055*** 0.031*** Inter-firm Cooperation 0.137*** 0.148*** 0.159*** 0.088*** Innovation Workers 0.180*** 0.241*** 0.186*** 0.120*** Size Classes 0.047*** 0.042*** 0.080*** 0.037*** 20 Sectors -0.001** -0.001 0.012*** -0.005*** Observations 27733 6829 9036 11868 Pseudo R-squared 0.128 0.117 0.123 0.124
  • 17. Category II – Product Innovations and macroeconomic dynamics VARIABLES Aggregate Aggregate Aggregate   marginal effects marginal effects marginal effects Domestic Consumption 0.003 Unemployment 0.007** Interest Rates -0.015** Assistance from External Networks 0.055*** 0.055*** 0.055*** Inter-firm Cooperation 0.137*** 0.137*** 0.137*** Workers Dedicated Towards Innovation Activities 0.181*** 0.181*** 0.181*** Size Classes 0.047*** 0.050*** 0.050*** 20 Sectors -0.001** -0.001** -0.001** Observations 27733 27733 27733 Pseudo R-squared 0.128 0.128 0.128 *** p<0.01, ** p<0.05, * p<0.1
  • 18. Conclusions
    • Category I : Product innovations seem to pro-cyclical to GDP [Innovation as Luxury] for most industries excluding the most innovative (Chemical, Metal, Wholesale Trade, and Food and Beverage) [Strategic Process ].
  • 19. Conclusions cont’d
    • Category II: Product innovations are pro-cyclical to domestic consumption [Innovation as Luxury] and unemployment [Access to Skilled Labor]. Evidence of [Constrained Finance ] Effect.
    • No evidence of counter-cyclical product innovations; No Creative Destruction evidence.
  • 20. Thank you and questions Neil Thompson