GROWINPRO – Growth, Welfare, Innovation, Productivity

Permanent URI for this collection

https://hdl.handle.net/10062/76373

GROWINPRO kodulehekülg.

GROWINPRO aims to provide a detailed analysis of the causes of the anaemic growth performance observed in Europe during the last decades and, in particular, after the Great Recession. On the grounds of such analysis, GROWINPRO will deliver a set of policy solutions aimed at restoring sustained and inclusive economic growth with particular attention both on the demand and on the supply-side.
GROWINPRO brings together researchers from eleven international academic institutions and three national statistical offices. The joint interaction between academic institutions and national statistical offices provides GROWINPRO with a focus on new data sources, methods and statistical indicators to address the challenges posed by the call.
The project has two main ambitions. From a diagnostic perspective, it proposes to link three levels of analysis – macro, meso and micro – empirically dissecting the sources of productivity slowdown and the relations between productivity, demand and growth. From a normative perspective, it aims at providing a novel, integrated set of policies to push Europe towards a balanced, innovation-fuelled and inclusive trajectory of development, also addressing major societal challenges, such as climate change, ageing population, and robotization.

Browse

Now showing 1 - 20 of 22

Predicting company innovativeness by analysing the website data of firms: a comparison across different types of innovation
(2022) Sõna, Sander; Masso, Jaan; Sharma, Shakshi; Vahter, Priit; Sharma, Rajesh
This paper investigates which of the core types of innovation can be best predicted based on the website data of firms. In particular, we focus on four distinct key standard types of innovation – product, process, organisational, and marketing innovation in firms. Web-mining of textual data on the websites of firms from Estonia combined with the application of artificial intelligence (AI) methods turned out to be a suitable approach to predict firm-level innovation indicators. The key novel addition to the existing literature is the finding that web-mining is more applicable to predicting marketing innovation than predicting the other three core types of innovation. As AI based models are often black-box in nature, for transparency, we use an explainable AI approach (SHAP - SHapley Additive exPlanations), where we look at the most important words predicting a particular type of innovation. Our models confirm that the marketing innovation indicator from survey data was clearly related to marketing-related terms on the firms' websites. In contrast, the results on the relevant words on websites for other innovation indicators were much less clear. Our analysis concludes that the effectiveness of web-scraping and web-text-based AI approaches in predicting cost-effective, granular and timely firm-level innovation indicators varies according to the type of innovation considered.
The relationship of technological and organizational innovation with firm performance: opening the black box of dynamic complementarities
(2022) Vahter, Priit; Vadi, Maaja
This paper explores the dynamic nature of complementarities between technological and organizational innovation at firms. Using Spanish firm level panel data (PITEC) over period 2008-2016, it investigates how the formation, keeping and ending of the joint adoption of these two core types of innovation is associated with firm performance. In the case of the general static test of complementarities we find no evidence of complementarities. However, once we focus on the analysis of within-firm changes in the complementarity bundle of innovation types, we observe clear evidence that some sequential as well as simultaneous strategy switches towards combining technological and organizational novelties are associated with significant performance premia at firms. Our findings point out the key role of technological innovation in these complementarities. We find evidence of sequential complementarity only when organizational innovation is added to the already existing technological innovation at the firm, not when organizational innovation is added as first component before technological innovation. In the case of dissolving the complementarity bundle of innovation types, the key disadvantage for the firm is related to dropping the technological innovation. Giving up only organizational innovation while keeping the technological innovation appears to have no negative effect, on average, on firm performance.
Productivity and firm dynamics over the business cycle
(2022) Assefa, Abraham; Lapitskaya, Darya; Uusküla, Lenno
The paper studies the effects of technology shocks on the creation and destruction of firms. Using US data and a VAR model the paper finds Schumpeterian creative destruction for investment-specific technology shocks. A positive investment-specific technology shock increases the number of firms opening, but also leads to a higher number of firms closing. In contrast, labour-neutral technology shocks also benefit old firms. An increase in overall productivity leads to an increase in the number of new firms and a drop in the number of failures. Both margins contribute to an increase in the number of firms in the economy. A medium-scale DSGE model with endogenous entry and exit that is that is augmented with additional features is able to capture these stylised facts.
The effects of the ECB communications on financial markets before and during COVID-19 pandemic
(2022) Alfieri, Luca; Eratalay, Mustafa Hakan; Lapitskaya, Darya; Sharma, Rajesh
The paper aims to estimate the effects of the European Central Bank communications on the sectoral returns of STOXX Europe 600 from 2013 to 2021. Previous literature has investigated the effects of communications of central banks and checked their effects on macroeconomics and financial data. New opportunities offered by text mining analysis allow us to find new insights into these aspects. However, studies focusing on how text mining indices derived from central banks’ communications can affect different financial sectors are more limited. In this paper, we use different sentiment and topic indices derived from the European Central Bank’s speeches. The paper shows how these different topics and sentiment indices affect the returns on different financial sectors. Our results indicate that the topic of communications is more influential on returns of sectoral indices than the type of communications. Moreover, we find that monetary policy and financial stability topics are the most relevant. We also find that during the COVID-19 time, the number of negative speeches is relevant for almost all the sectoral index returns.
Predicting stock returns: ARMAX vs. machine learning
(2022) Lapitskaya, Darya; Eratalay, Hakan; Rajesh Sharma
In the modern world, online social and news media significantly impact society, economy, and financial markets. In this chapter, we compared the predictive performance of financial econometrics and machine learning and deep learning methods for the returns of the stocks of the SP100 index. The analysis is enriched by using COVID-19 related news sentiments data collected for a period of 10 months. We analyzed the performance of each model and found the best algorithm for such types of predictions. For the sample we analyzed, our results indicate that the autoregressive moving average model with exogenous variables (ARMAX) has a comparable predictive performance to the machine and deep learning models, only outperformed by the extreme gradient boosted trees (XGBoost) approach. This result holds both in the training and testing datasets.
Role of institutions in the corruption and firm innovation nexus: evidence from former Soviet Union countries
(2022) Aghazada, Elchin; Ashyrov, Gaygysyz
In view of the missing consensus on how corruption relates to firm innovation, this paper empirically studies the relationship between petty corruption and product, process, marketing and organizational innovations in the post-Soviet region. Exploiting cross-sectional firm-level data from the fifth round of the Business Environment and Enterprise Performance Survey (BEEPS V), the paper argues that institutional context has utmost importance when approaching this link. Probit estimations for a full sample of post-Soviet countries indicate a positive link between bribes and firm innovation. Considering variations in institutional development levels, the paper distinguishes three clusters of countries within the region with respect to the quality of institutional structures based on Worldwide Governance Indicators (WGI) data from the World Bank. The results reveal that the grease-the-wheel effect of bribery on firm innovation strongly remains in countries with weak institutional quality. To explore this link further, the paper made several additional estimations and robustness checks.
The impact of ESG ratings on the systemic risk of European blue-chip firms
(2022) Eratalay, Mustafa Hakan; Cortés Ángel, Ariana Paola
There are diverging results in the literature on whether engaging in ESG related activities increases or decreases the financial and systemic risks of firms. In this paper we explore whether maintaining higher ESG ratings would reduce the systemic risks of firms in a stock market context. For this purpose we analyse the systemic risk indicators of the constituent stocks of S&P Europe 350 for the period of January 2016 - September 2020, which also partly covers the Covid-19 period. We apply a VAR-MGARCH model to extract the volatilities and correlations of the return shocks of these stocks. Then we obtain the systemic risk indicators by applying a principle components approach to the estimated volatilities and correlations. Our focus is on the impact of ESG ratings on systemic risk indicators, while we consider network centralities, volatilities and financial performance ratios as control variables. We use fixed effects and OLS methods for our regressions. Our results indicate that (1) the volatility of a stock’s returns and its centrality measures in the stock network are the main sources contributing to the systemic risk measure (2) firms with higher ESG ratings face up to 7.3% less systemic risk contribution and exposure compared to firms with lower ESG ratings, (3) Covid-19 augmented the partial effects of volatility, centrality measures and some financial performance ratios. When considering only the Covid-19 period, we found that social and governance factors have statistically significant impacts on systemic risk.
New member in the boardroom and subsequent strategic change in the product-market scope of the firm
(2020) Süsi, Virgo; Lukason, Oliver
Purpose – The purpose of this paper is to explore the linkages between the appointment of a new management board member and the following strategic change in the product-market scope of the firm. Design/methodology/approach – The study is based on the whole population of Estonian firms, in total 16,941 observations, and the data is retrieved from Estonian Business Register. First, we focus on the association between the appointment of a new board member and the likelihood of different types of strategic change. Second, we focus on the association between the new board member’s previous export experience and the export related strategic change. Logistic regressions are applied for all models. Findings – The results indicate that there is a significant association between the appointment of a new board member and the subsequent start of exports and also continuing it, entrance into a new industry and making a strategic change in more broad terms, though the significance levels vary across the composed models. No significant relationship was found with the entrance into additional geographic market(s) for already exporting firms. There was also a significant association between previous export experience of a new board member and subsequent start of exporting. Originality/value – We look at strategic change in the product-market domain holistically by applying same data on both geographic and product portfolio expansion options. We also introduce the scale and stability contexts of strategic changes. These aspects are usually neglected from similar studies.
Churning and labor productivity in economic crisis, differences between foreign and domestic firms
(2021) Roosaar, Liis; Varblane, Urmas; Masso, Jaan
Our analysis of matched employee-employer data from Estonian firms (years 2006–2013) shows that an increase in labor churning is related to a positive change in labor productivity during an economic crisis. During boom years, churning is related to a negative change in labor productivity. Only in services during the crisis did foreign firms have a stronger positive relationship between labor churning and labor productivity changes than domestic firms. However, our analysis at the individual level does not confirm that, during a crisis, foreign firms in services hire more employees with characteristics that have been found to be related to productivity increases.
Predicting stock return and volatility with machine learning and econometric models: A comparative case study of the Baltic stock market
(2021) Nõu, Anders; Lapitskaya, Darya; Eratalay, Mustafa Hakan; Sharma, Rajesh
For stock market predictions, the essence of the problem is usually predicting the magnitude and direction of the stock price movement as accurately as possible. There are different approaches (e.g., econometrics and machine learning) for predicting stock returns. However, it is non-trivial to find an approach which works the best. In this paper, we make a thorough analysis of the predictive accuracy of different machine learning and econometric approaches for predicting the returns and volatilities on the OMX Baltic Benchmark price index, which is a relatively less researched stock market. Our results show that the machine learning methods, namely the support vector regression and k-nearest neighbours, predict the returns better than autoregressive moving average models for most of the metrics, while for the other approaches, the results were not conclusive. Our analysis also highlighted that training and testing sample size plays an important role on the outcome of machine learning approaches.
Does corruption hinder firm energy efficiency? Evidence from Vietnam
(2022) Ashyrov, Gaygysyz; Poltimäe, Helen
Energy efficiency is an important issue for developing countries like Vietnam, where the economy is thriving, but energy efficiency is still low. Firms should invest in energy efficiency measures, but the desired level is not reached. While the economic determinants of firms’ investments in energy efficiency have been researched, the role of the institutional setting has not gained so much attention. By employing data from Vietnamese small and medium-sized enterprises that has been administered in 2015, this article investigates how corruption, as a sign of institutional dysfunctionality, is associated with the energy efficiency in firms. Results of a bivariate binary probit estimation revealed that bribery increases the likelihood of energy efficiency environmentally friendly investments. However, findings from instrumental variable two stage least squares estimations demonstrate that bribery increases the cost of the investments. Hence, in the long run, corruption might have a deterring effect on energy efficiency investments by firms.
Academic assets, life-cycle, and entrepreneurship: a longitudinal study of Estonian academic workers
(2021) Mõttus, Maksim; Lukason, Oliver
This study aimed to find out how academic assets are interconnected with firm creation by academic staff at different academic life-cycle stages. The applied theoretical setting integrated resource-based and life-cycle explanations of academic entrepreneurship. A longitudinal whole population dataset of Estonian academic workers was applied, with a dependent variable reflecting firm creation, and independent variables representing different academic assets. The logistic regression results indicated the varying importance of different academic assets at different academic career stages, while divergence also exists with respect to academic discipline. The results enable postulating several theoretical propositions, accompanied by practical implications for technology transfer at universities.
How does managerial experience predict the internationalization type of a young firm?
(2021) Lukason, Oliver; Vissak, Tiia; Segovia-Vargas, Maria-Jesus
This study aims to find out how useful managers' past general and export experience is in predicting whether young manufacturing firms become fast internationalizers. Extant literature about the role of managerial experience in determining young firms' internationalization type is scant. This paper fills this gap by providing systematic evidence on which kinds of general and export experience can be used for accurate predictions of two firm types: born globals and general fast internationalizers. Our dataset encompasses information about managerial experience of the whole population of young Estonian manufacturing firms. Based on using four different prediction methods (logistic regression, rough sets, decision tree, neural networks) and a large variety of variables reflecting managers' past experience, the results indicate that in prediction models, export experience variables are more valuable than general experience variables. Born globals can be predicted with an accuracy of at least 90% in case of all applied machine learning methods, while the precision is lower in case of general fast internationalizers. The study leads to important implications for international business theory and practice.
Deep diving into the S&P Europe 350 index network and its re-action to COVID-19
(2021) Cortés Ángel, Ariana Paola; Eratalay, Mustafa Hakan
In this paper, we analyse the dynamic partial correlation network of the constituent stocks of S&P Europe 350. We focus on global parameters such as radius, which is rarely used in financial networks literature, and also the diameter and distance parameters. The first two parameters are useful for deducing the force that economic instability should exert to trigger a cascade effect on the network. With these global parameters, we hone the boundaries of the strength that a shock should exert to trigger a cascade effect. In addition, we analysed the homophilic profiles, which is quite new in financial networks literature. We found highly homophilic relationships among companies, considering firms by country and industry. We also calculate the local parameters such as degree, closeness, betweenness, eigenvector, and harmonic centralities to gauge the importance of the companies regarding different aspects, such as the strength of the relationships with their neighbourhood and their location in the network. Finally, we analysed a network substructure by introducing the skeleton concept of a dynamic network. This subnetwork allowed us to study the stability of relations among constituents and detect a significant increase in these stable connections during the Covid-19 pandemic.
Do firms really learn from failure? The dynamics of abandoned innovation
(2020) Love, James; Roper, Stephen; Vahter, Priit
Abandoned and failed innovations can be regarded as a part of the natural process of experimentation by firms, which can lead to important lessons being learned. Although the literature suggests some benefit from failure or abandoned innovation activities, prior studies using relatively large firm-level datasets to test the nature of this link are often unable to deal explicitly with the time dimension of learning. We contribute to the literature by showing the dynamic and causal nature of the linkage between abandoned innovation and subsequent innovation outcomes at firms. We demonstrate based on balanced panel data of Spanish manufacturing firms from 2008-2016 that innovation failure not only leads to more successful innovation, but that there is an explicit time dimension to this. We demonstrate that firms which have experienced ‘failure’ (as evidenced by abandoned innovation activities) in the past will have stronger positive effects of recent abandoned innovation activities on innovation output. This is a strong test of the ‘learning-from-failure’ hypothesis. In addition, we find evidence that in addition to enabling cumulative learning processes, abandoning innovation may also act as a dynamic corrective mechanism preventing firms carrying weaker innovation portfolios through from one period to the next.
The role of firms in the gender wage gap
(2020) Masso, Jaan; Meriküll, Jaanika; Vahter, Priit
Recent research suggests that firm-level factors play a significant role in the gender wage gap. This paper adds to this literature by analysing the role of sorting between firms and bargaining within firms using the methodology of Card et al. (2016). We employ linked employer-employee data for the whole population of firms and employees from Estonia for 2006–2017. Estonia is a country with the highest gender wage gap in the EU with about two-thirds of that unexplained by conventional factors. The results show that firm-level factors are important determinants of the gender wage gap, explaining as much as 35% of the gap. We find that within-firm bargaining plays a larger role in the gender wage gap than similar prior papers. This could be related to lenient labour market institutions, as reflected in low minimum wages and union power, and to lower bargaining skills of women. Further, the role of firm-level factors in the gender wage gap have increased over time, and these are especially important at the top of the wage distribution and among workers that are more skilled. There is a heavy penalty for motherhood in wages, 4–9 log points, but this is not related to firm-specific time-invariant productivity premiums.
Productivity gains from labour churning in economic crisis: do foreign firms gain more?
(2020) Roosaar, Liis; Varblane, Urmas; Masso, Jaan
The purpose of this paper is to clarify whether domestic or foreign firms gained more from labour churning while adjusting to the Great Recession in Estonia. During times of high unemployment, all firms can raise their requirements for new employees, but in times of crisis foreign firms may have more resources available for restructuring. We analysed matched employee-employer data from Estonian firms from 2006 to 2013, and show that an increase in labour churning is related to a positive change in labour productivity during economic crisis. During boom years churning is related to a negative change in labour productivity. In both cases a slightly upward convex pattern can be noticed. Only in services during the crisis did foreign firms have a stronger positive relationship between labour churning and labour productivity changes than domestic firms. However, our analysis at the individual level does not confirm that during a crisis foreign firms hire more employees with characteristics that have been found to be related to productivity increases. We also show empirically that hiring employees who relatively often change jobs is negatively related to changes in labour productivity. In light of the world-wide virus-related crisis of 2020, this paper proves that economic downturns can be a good opportunity to restructure the pool of employees.
Corruption and firm innovation: evidence from post-Soviet countries
(2021) Aghazada, Elchin; Ashyrov, Gaygysyz
In view of the missing consensus on how corruption relates to firm innovation, this paper empirically studies the relationship between petty corruption and product, process, marketing and organizational innovations in the post-Soviet region. Exploiting crosssectional firm-level data from the fifth round of the Business Environment and Enterprise Performance Survey (BEEPS V), the paper argues that institutional context has utmost importance when approaching this link. Probit estimations for a full sample of post-Soviet countries indicate a positive link between bribes and firm innovation. Considering variations in institutional development levels, the paper distinguishes three clusters of countries within the region with respect to the quality of institutional structures based on Worldwide Governance Indicators (WGI) data from the World Bank. The results reveal that the greasethe- wheel effect of bribery on firm innovation strongly remains in countries with weak institutional quality. To explore this link further, the paper made several additional estimations and robustness checks.
Productivity implications of R&D, innovation, and capital accumulation for incumbents and entrants: the case of Estonia
(2021) Masso, Jaan; Tiwari, Amaresh
In this paper, using Estonian Community Innovation Survey data, we study the role of R&D, capital accumulation, and innovation output on pro- ductivity for entrants and incumbents. We find that the impact of R&D invest- ment on labour productivity is larger for the entrants compared to the incum- bents. Entrants are found to be more productive and more heterogeneous in their total factor productivity (TFP) than the incumbents. Moreover, entrants who innovate are on average, in terms of TFP, 25% more productive than the entrants who do not, while the corresponding figure for the incumbents is 7%. In addition, it is mostly the incumbents who benefit from within-industry knowledge that is produced outside their own firm. Finally, for both entrants and incumbents, em- bodied technological change through capital accumulation is found to be more effective in generating productivity growth than R&D expenditure.
Effects of automation on the gender pay gap: the case of Estonia
(2021) Pavlenkova, Ilona; Alfieri, Luca; Masso, Jaan
This paper investigates how investments in automation-intensive goods affects the gender pay gap. The evidence on the effects of automation on the labour market is growing; however, little is known about the implications of automation for the gender pay gap. The data used in the paper are from a matched employer-employee dataset incorporating detailed information on firms, their imports, and employee-level data for Estonian manufacturing and services employers for 2006–2018. We define automation using the imports of intermediates embedding automation technologies. The effect of automation is estimated using simple Mincerian wage equations and the causality of the effect is validated using propensity score matching. We find that introducing automation enlarges the gender pay gap. The negative effect of importing automation-intensive goods for female employees is about two to four percentage points larger than for male employees. The propensity score matching confirms that the introduction of automation has a higher causal effect on the wages of male employees than female employees.

Browse

Recent Submissions