Do the Sub-saharan Africa economies with volatile GDP promote innovation? Yaya KY UCAD/CRES François Joseph CABRAL UCAD/CRES

SUMMARY Objective stylized Facts Methodology Results

Objective We aim to show in this paper that the accumulation of innovation and knowledge through their production or absorption can be strong and sustainable factors of GDP growth.

Stylized facts In most Sub-saharan Africa economies, economic growth is mostly driven by the export of low value- added commodities. A dozen commodities (Cocoa, coffee, oil, gas, cotton, mining,…) represent 80% of total exports.

Stylized facts In general, the trend of GDP growth is not correlated with the level of innovation of the economy even if the average GDP growth rate seems to be correlated with innovation for some economies. However, the volatility of GDP growth, measured by standard deviation is correlated with innovation.²

Stylized facts Graph 1: Link between coefficient of variation of GDP growth rate, innovation index and TFP

Stylized facts The economic literature (aghion,2014; dinopoulos,1999; jones,1995; kortum,1997; Peretto,1998; segerstrom,1998; young,1999) finds a positive correlation between the productivity growth and the share of research and development in GDP i.e. the magnitude of innovation activities and knowledge accumulation. Empirically, the mains contributions can be aggregate under tree perspectives 1.The identification of source of macroeconomic volatility; (Guillaumont,2010; loayza and Raddatz, 2007 ; combes, 2002, Fata and Mihov,2006, 2007) 2.The measure of macroeconomic volatility (Dehn,2000; Chauvet and becker,2006; Hnatkovska and Loayza, 2005; afonso,2010; Serven,1997) 3.The assessment of the impact of macroeconomic volatility on economic development (Dawe,1996; Dehn,2000; guillaumont;1999; Koren and Tenreyro,2006)

Methodology The volatility index vt at time t is define as: is the log of GDP of the balanced growth path where Where gl is the GDP growth rate at time l. The model with interaction term estimate is :

Methodology The volatility can be expressed in terms of GDP per capita. The parameter lambda is a specific volatility coefficient of each country. It is a function of innovation. From this equation, an economy can control the level of volatility of GDP if and only if the volatility depends on GDP per capita and lambda is negative. Control the volatility depends on the level of innovation if

Methodology Five specifications are estimated: 1.The first model builds on all the countries for which data are available 2.The second model take into account the financial development of the country. Financial development is captured as the volume of private sector credit in term of GDP. 3.The third model includes an interaction term between GDP per capita and innovation index 4.The fourth model concern only the Sub-saharan Africa countries 5.The last model uses the previous model and includes an interaction term between GDP per capita and innovation index All these models are estimated with general moment method (GMM)proposed by Arellano and Bond (1991). The estimation take into account the robust option. The data source are: : World Development Indicator ; World productivity Base (WPB)

Results The level of volatility is related to that of the innovation. This level is particularly volatile for economies whose innovation index is 1 or 2; For these economies, volatility of the rate of GDP growth is higher and ranking from 4% to 6% of GDP. The economies with innovation index equal to 7 have a volatility equal to 4% of GDP at the beginning of the period and declines to 2% at the beginning of the millennium. The economies whose level of innovation is 8 or 9 have the lowest level of volatility. This is a trend hovering around 2% GDP.

Results Graph2: GDP volatility by innovation index (world)

Results For most Sub-saharan Africa economies, the volatility of GDP growth rate exceeds 3% of GDP Graph3: GDP volatility by innovation index (africa)

Results Table 1: Estimation results

Results Innovation is a factor of resilience of instability of GDP. All models show that innovation has a significant effect on the volatility of GDP. The effect is negative in models without interaction term between GDP per capita and innovation index. The interaction term (βiny ) is negative and corresponds to for the model estimated on all countries and for the model estimated on Sub-saharan Africa countries.

Results Graph4: Confidence interval of innovation impact on volatility

Results Most other regions have a less volatile growth rate than countries in sub- Saharan Africa. The threshold of GDP per capita from which a marginal change in the index of innovation reduces volatility is US $ 6,374.1 for all countries. Its 90% confidence interval is [US $ US $ 171,099.4]. Countries whose GDP per capita is less than this threshold represents 56% for all countries and 87% for countries in sub-Saharan Africa. This threshold is US $ for sub-Saharan Africa countries with a confidence interval [US $ $ 2,123.6 UD].

Conclusion The objective of the paper is to assess the impact of innovation on volatility of GDP in economies in sub-Saharan Africa. We built a volatility index of the rate of GDP growth and assessed the impact of innovation on this index using dynamic panel model. Countries that do not produce enough innovation have a GDP growth rate that is highest but most volatile compare to countries that promote innovation. In addition, countries whose coefficient of variation is weakest have an innovation index higher and a Total Factor Productivity (TFP) substantial. Estimates show that innovation reduces the volatility of the GDP growth rate.

Conclusion The findings bring the proof that innovation is a resilience factor of volatility of the rate of GDP growth. Countries with less income, in general, and sub-Saharan Africa countries in particular whose economy are victim of exogenous shock can promote knowledge accumulation to control the instability of their GDP growth. Because the process of innovation is long, expensive and irreversible, these countries can identify knowledge which benefits their economy. They should identify the main means that allow them to produce innovation, and develop policy to absorb them

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