Summary of empirical studies on firms' export intensity
| Author (year) | Country (period) | Number of firms | Estimation method | Explanatory variables | Control variables |
|---|---|---|---|---|---|
| Kim and Hemmert (2016) | Korea (2010) | 1,733 | Tobit model | Technological, marketing and financial resources; Executives' managerial capabilities; Subcontracting network ties | Firm's age, size and financial performance; Industry dummies |
| Reis and Forte (2016) | Portugal (2010–2013) | 19,504 | Tobit model; RE; HE | Industry characteristics (capital intensity, R&D intensity, concentration, export orientation and labour productivity) | Firm's age, size and labour productivity |
| Gajewski and Tchorek (2017) | Poland (2013) | More than 730 | OLS; Huber–White Sandwich estimator | Family control, firm size, foreign control, introduction of innovative products and processes (all binary variables) | Year of birth; Number of declared non-cost factors of success (quality of products, diversified product offer, brand recognition, developed distribution chain, post sales services); Firm run by owner (dummy variable) |
| Tyagi and Nauriyal (2017) | India (2000–2014) | Top 91 publicly listed firms | GMM | Innovative activities (R&D intensity); Past innovative output (patents) | Firm's age and size |
| Zucoloto et al. (2017) | Brazil (2001–2003, 2003–2005 and 2006–2008) | 1,639 observations | OLS; FE | IP-related appropriation strategies (invention patents, utility models, industrial designs and trademarks) | Firm's characteristics such as origin of capital (national/foreign), size, innovative expenditures and age; Industry dummies |
| Krammer et al. (2018) | BRIC countries (2015) | 16,748 firms | HE | Political instability, informal competition and corruption; Firm capabilities (skill level of the workforce, managerial capabilities, external technological capabilities) | Firm's age, size, ownership (foreign, public), quality of workforce; Country and industry dummies |
| Nam et al. (2018) | Korea (2001–2007) | 642 non-financial listed firms | HE | Board directors' work experience in government and MNEs; Proportion of outside directors | Firm's characteristics such as size, number of board members, R&D over total sales, advertising expenditures over total sales and leverage; Year and industry dummies |
| Bashiri Behmiri et al. (2019) | Portugal (2014/2015) | 214/213 | OLS; Tobit model | Firm characteristics (size, age and productive efficiency) | The type of produced wines (Port wine/Douro wine) |
| Chung et al. (2019) | China (2004/2006) | 229 | n.a | Prior export sales intensity | Firm's age, size, financial performance, innovation; Dummy variables to control for manufacturing firms, high-tech firms, firms transformed from a state-owned enterprise, and managing structure |
| Bekteshi (2020) | Republic of Kosovo (2012) | 500 | Tobit model | Firm's size | - |
| Carboni and Medda (2020) | 7 European countries (2007/2009) | 14,797 | System equation regressions; HE | Innovation and tangible investment | Firm's age and size; Dummy variables indicating: whether the firm had exported before, if the firm is part of a group and if the firm is head of a group; Country and industry dummies |
| Faria et al. (2020) | Portugal (2014–2016) | 412 wine-producing firms | HE; Fractional probit and two-part fractional response model | Firm characteristics (size, age, labour productivity); Dummy variable to control for the benefits of public funding | Firm's debt capacity; Country-wide level of exports to control for the dynamics of export activity |
| López Rodríguez et al. (2020) | Spain (2014) | 1,525 manufacturing firms | Logit and tobit models | Firms' general and specific human capital | Firm's age, size, R&D intensity; Dummy variables to control for: belonging to a business group and participation of foreign capital; Industry dummies |
| Sharma et al. (2020) | China (2006–2010) | 1,945 firms listed on Shanghai and Shenzhen stock exchanges | Multiple regression analysis | Political connections (political relationships of all board members) | Firm characteristics (size, age, leverage, ratio of market to book values of equity, total factor productivity); Firm's ownership type; Competitive pressure (Herfindahl index); Industry and year dummies |
| Woo et al. (2020) | Korea (2015) | 1,968 | Multiple regression analysis and hierarchical regression analysis methods | Firm capabilities (entrepreneurship, marketing capability, network capabilities, customer capability, product differentiation, human resources, financial, and R&D) | Firm's age and size |
| Charoenrat and Amornkitvikai (2021) | China (2012) | 1,500 | Tobit model | Firm size, skilled labour, % of foreign ownership; Dummy variables for firm location, female CEO, R&D, innovation and technology import | (*) |
| Dong et al. (2021) | China (2008–2017) | 1,156 listed private firms | Tobit model | Performance feedback (i.e. a focal firm's performance relative to its industry peers); Institutional development and political connections | Chairman age, female CEO and top management team overseas experience; Firm size, state share, foreign ownership, firm slack, firm location (special economic zone or open coastal city); Industry competition (Herfindahl index) and industry export orientation |
| Haddoud et al. (2021) | Poland (2019) | 409 | Non-linear partial least squares structural equation modelling | Environmental commitment, product and process innovation | Firm size, sector and region |
| Talukder and Tripathi (2021) | India (2009/2010 to 2018/2019) | Top 53 firms from pharmaceutical industry | FE | Supply chain performance (return on supply chain fixed assets, return on working capital, all expenditures involved with the supply chain, including the purchasing costs and the selling and distribution costs, and raw material import intensity) | - |
| Castellani et al. (2022) | 46 countries (2015) | 13,131 | Ordered logit model | Early-stage financing diversity (financing diversity index); Institutional context in terms of financial development and investor protection | Managerial education, managerial experience, number of firm owners, technological level, reasons for starting a business activity; Competition; Country dummies |
| Author (year) | Country (period) | Number of firms | Estimation method | Explanatory variables | Control variables |
|---|---|---|---|---|---|
| Korea (2010) | 1,733 | Tobit model | Technological, marketing and financial resources; Executives' managerial capabilities; Subcontracting network ties | Firm's age, size and financial performance; Industry dummies | |
| Portugal (2010–2013) | 19,504 | Tobit model; RE; HE | Industry characteristics (capital intensity, R&D intensity, concentration, export orientation and labour productivity) | Firm's age, size and labour productivity | |
| Poland (2013) | More than 730 | OLS; Huber–White Sandwich estimator | Family control, firm size, foreign control, introduction of innovative products and processes (all binary variables) | Year of birth; Number of declared non-cost factors of success (quality of products, diversified product offer, brand recognition, developed distribution chain, post sales services); Firm run by owner (dummy variable) | |
| India (2000–2014) | Top 91 publicly listed firms | GMM | Innovative activities (R&D intensity); Past innovative output (patents) | Firm's age and size | |
| Brazil (2001–2003, 2003–2005 and 2006–2008) | 1,639 observations | OLS; FE | IP-related appropriation strategies (invention patents, utility models, industrial designs and trademarks) | Firm's characteristics such as origin of capital (national/foreign), size, innovative expenditures and age; Industry dummies | |
| BRIC countries (2015) | 16,748 firms | HE | Political instability, informal competition and corruption; Firm capabilities (skill level of the workforce, managerial capabilities, external technological capabilities) | Firm's age, size, ownership (foreign, public), quality of workforce; Country and industry dummies | |
| Korea (2001–2007) | 642 non-financial listed firms | HE | Board directors' work experience in government and MNEs; Proportion of outside directors | Firm's characteristics such as size, number of board members, R&D over total sales, advertising expenditures over total sales and leverage; Year and industry dummies | |
| Portugal (2014/2015) | 214/213 | OLS; Tobit model | Firm characteristics (size, age and productive efficiency) | The type of produced wines (Port wine/Douro wine) | |
| China (2004/2006) | 229 | n.a | Prior export sales intensity | Firm's age, size, financial performance, innovation; Dummy variables to control for manufacturing firms, high-tech firms, firms transformed from a state-owned enterprise, and managing structure | |
| Republic of Kosovo (2012) | 500 | Tobit model | Firm's size | - | |
| 7 European countries (2007/2009) | 14,797 | System equation regressions; HE | Innovation and tangible investment | Firm's age and size; Dummy variables indicating: whether the firm had exported before, if the firm is part of a group and if the firm is head of a group; Country and industry dummies | |
| Portugal (2014–2016) | 412 wine-producing firms | HE; Fractional probit and two-part fractional response model | Firm characteristics (size, age, labour productivity); Dummy variable to control for the benefits of public funding | Firm's debt capacity; Country-wide level of exports to control for the dynamics of export activity | |
| Spain (2014) | 1,525 manufacturing firms | Logit and tobit models | Firms' general and specific human capital | Firm's age, size, R&D intensity; Dummy variables to control for: belonging to a business group and participation of foreign capital; Industry dummies | |
| China (2006–2010) | 1,945 firms listed on Shanghai and Shenzhen stock exchanges | Multiple regression analysis | Political connections (political relationships of all board members) | Firm characteristics (size, age, leverage, ratio of market to book values of equity, total factor productivity); Firm's ownership type; Competitive pressure (Herfindahl index); Industry and year dummies | |
| Korea (2015) | 1,968 | Multiple regression analysis and hierarchical regression analysis methods | Firm capabilities (entrepreneurship, marketing capability, network capabilities, customer capability, product differentiation, human resources, financial, and R&D) | Firm's age and size | |
| China (2012) | 1,500 | Tobit model | Firm size, skilled labour, % of foreign ownership; Dummy variables for firm location, female CEO, R&D, innovation and technology import | (*) | |
| China (2008–2017) | 1,156 listed private firms | Tobit model | Performance feedback (i.e. a focal firm's performance relative to its industry peers); Institutional development and political connections | Chairman age, female CEO and top management team overseas experience; Firm size, state share, foreign ownership, firm slack, firm location (special economic zone or open coastal city); Industry competition (Herfindahl index) and industry export orientation | |
| Poland (2019) | 409 | Non-linear partial least squares structural equation modelling | Environmental commitment, product and process innovation | Firm size, sector and region | |
| India (2009/2010 to 2018/2019) | Top 53 firms from pharmaceutical industry | FE | Supply chain performance (return on supply chain fixed assets, return on working capital, all expenditures involved with the supply chain, including the purchasing costs and the selling and distribution costs, and raw material import intensity) | - | |
| 46 countries (2015) | 13,131 | Ordered logit model | Early-stage financing diversity (financing diversity index); Institutional context in terms of financial development and investor protection | Managerial education, managerial experience, number of firm owners, technological level, reasons for starting a business activity; Competition; Country dummies |
Note(s): (*) the authors did not distinguish between explanatory and control variables; BRIC - Brazil, Russia, China and India; CEO – Chief executive officer; FE – Fixed effects model; GMM – Generalized method of moments; HE - Heckman two-stage method; IP - Intellectual property; R&D – Research and development; RE – Random effects model
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