Job Creation and Job Destruction in Economic Crisis at Firm Level: The Case of Greek Manufacturing sectors

Transcription

1 Job Creation and Job Destruction in Economic Crisis at Firm Level: The Case of Greek Manufacturing sectors F. Voulgaris, Technological Educational Institute of Crete, Greece G. Agiomirgianakis Hellenic Open University Greece Abstract Th. Papadogonas Technological Educational Institute of Chalkis, Greece The current European economic crisis changes radically the structure of present and future employment, the political agenda and the adoption of appropriate economic policy means in the whole Europe. This is mostly true for southern European countries that were hit hard by economic crisis and thus raising questions about the appropriate policy mix required in supporting employment. In Greece, for example, the problem of unprecedented large unemployment (27%) by summer 2013, is an urgent issue dominating in all current discussions related to adoption of the best economic policy means. Often, these discussions are focused on some general macroeconomic policy suggestions that are not based on a microeconomic analysis of how firms are affected by economic crisis, not only, in the same sector, but also, in different sectors of the economy. In this study, we explore the determinants of job creation and job destruction using a large and comprehensive panel data set of Greek manufacturing firms, covering the time period and distinguishing between the pre-crisis ( ) and post-crisis ( ) period. Our study reveals that, although the crisis has indeed a substantial negative effect on employment growth in all sectors of Greek manufacturing, some sectors (such as food products) are less affected compared to others (especially textiles, wearing apparel and leather products). Thus, our results suggest that a discretionary microeconomic policy that could encourage production and exports, with such measures as tax reductions, investment subsidies, export grants, etc., in favour of the less affected sectors could contribute to reducing large unemployment. Keywords: Industry study, dynamic growth, manufacturing, financial performance JEL Classification: C23, D21, G32, J23, L11, L6 Acknowledgements: We would like to thank participants at the EEFS2013 conference in Berlin for valuable comments and useful suggestions that have improved the quality of this study. This research has been cofinanced by the European Union (European Social Fund ESF) and Greek national funds through the Operational Program "Education and Lifelong Learning" of the National Strategic Reference Framework (NSRF) - Research Funding Program: ARCHIMEDES III (code no ). Investing in knowledge society through the European Social Fund.

2 1. Introduction After the economic crisis of 2008, unemployment has become the major issue for all EU countries. The current European economic crisis changes radically the structure of present and future employment, the political agenda and the adoption of appropriate economic policy means in the whole Europe. This is mostly true for South European countries and especially for Greece which has suffered a severe recession during the last five years with an unprecedented large unemployment rate of 27% (50% for young people) by summer of , expected to climb up to 34% by As a result of this, studies dealing with the issues of job creation and the factors affecting it have attracted the interest of researchers and policy makers. Research is focused on some general macroeconomic policy suggestions that are not based on a microeconomic analysis of how firms are affected by economic crisis, not only, in the same sector, but also, in different sectors of the economy. In this study, we explore the determinants of job creation and job destruction using a large and comprehensive panel data set of Greek manufacturing firms, covering the time period and distinguishing between the pre-crisis ( ) and post-crisis ( ) period and compare empirical results with previous studies on the Greek manufacture for the before 2000 period. The sample includes 1400 private firms of corporate forms for which we had data for eight consecutive years, from all manufacturing sectors. The present study contributes to the existing literature in three ways: First we examine the determinants of employment growth in the Greek manufacturing, during the last 10 years, extending on previous research. Second, we detect differences in employment growth between the pre and after crisis period and third, we investigate the negative effect of economic crisis on employment among manufacturing sectors. Greek manufacture has suffered an unprecedented decrease of its growth, caused by a 30% fall of GDP 2 and needs urgently policies that will help restart its economic activity and reducing its unemployment rate. Whatever economic or political system a country is built upon, the fact remains that manufacturing will play a key role in its prosperity. Services not built on a vibrant manufacturing sector will not lift or sustain a nation s economy. Furthermore, new economic developments after the economic crisis and the strong competition arising from globalization have changed the employment structure and the factors 1 See e.g. ELSTAT 2 Greek GDP has shrunk by almost 30% since end 2007, i.e., before the beginning of the crisis (authors estimation based on European Commission AMECO database data).

3 affecting employment growth, especially in small developing countries, like Greece. Greece has suffered from deindustrialization as a result of manufacturing decline (Pitelis and Antonakis, 2003), while growth of manufacturing is regarded as a vital element in the sustainability of economic recovery; hence Greece is a hot topic these days Looking at the table 1 below, we see that the most important sectors in terms of employment in Greece are agriculture, manufacturing and trade. Out of 17,17% total average employment decrease for all the industrial sectors in Greece, for the period , we can see that the highest decrease was in the construction industry (47,9%) and real estate (34%), followed by manufacturing (32,9%) and mining (35,3%). Table 1. Employment by industry sector, Greece, % of Total, 2008 % of Total, 2012 Rate of growth Agriculture, forestry and fishing 478,0 497,8 511,8 472,6 466,0 10,69% 12,58% -2,51% Mining and quarrying 17,3 14,5 13,6 11,5 11,2 0,39% 0,30% -35,26% Manufacturing 533,1 509,0 465,6 412,2 357,7 11,92% 9,65% -32,90% Electricity, gas, steam and air conditioning supply 34,7 28,6 26,2 24,7 26,5 0,78% 0,72% -23,63% Water supply; sewerage, waste management and remediation activities 30,4 30,2 32,7 26,5 22,0 0,68% 0,59% -27,63% Construction 392,6 365,6 318,6 247,3 204,4 8,78% 5,52% -47,94% Wholesale and retail trade; repair of motor vehicles and motorcycles 816,3 801,4 783,6 745,8 663,3 18,25% 17,90% -18,74% Transportation and storage 210,1 213,3 207,5 197,9 182,1 4,70% 4,91% -13,33% Accommodation and food service activities 309,1 308,4 299,6 289,1 269,3 6,91% 7,27% -12,88% Information and communication 74,6 83,9 85,2 75,0 72,9 1,67% 1,97% -2,28% Financial and insurance activities 117,8 111,9 114,7 114,2 112,3 2,63% 3,03% -4,67% Real estate activities 8,8 8,4 6,1 5,5 5,8 0,20% 0,16% -34,09% Professional, scientific and technical activities 228,2 225,6 212,6 212,5 218,0 5,10% 5,88% -4,47% Administrative and support service activities 75,2 72,6 73,3 76,1 67,8 1,68% 1,83% -9,84% Public administration and defence; compulsory social security 375,9 373,8 369,6 358,0 333,5 8,40% 9,00% -11,28% Education 318,5 323,7 320,0 305,8 293,9 7,12% 7,93% -7,72% Human health and social work activities 230,2 228,9 241,5 236,2 224,4 5,15% 6,06% -2,52% Arts, entertainment and recreation 57,1 52,1 47,8 47,2 41,1 1,28% 1,11% -28,02% Other service activities 89,8 84,4 85,8 83,9 75,5 2,01% 2,04% -15,92% Activities of households as employers; undifferentiated goods- and servicesproducing activities of households for own use 74,2 87,4 89,1 72,6 55,8 1,66% 1,51% -24,80% Activities of extraterritorial organisations and bodies 1,6 1,6 1,6 2,2 1,9 0,04% 0,05% 18,75% TOTAL 4.473, , , , ,4 100% 100% -17,17%

4 Table 2. Employment by 2-digit manufacturing industry, % of Total, 2008 % of Total, 2012 Rate of growth Manufacture of food products 19,77% 26,99% -8,44% Manufacture of beverages 2,04% 2,60% -14,68% Manufacture of tobacco products 0,60% 0,78% -12,50% Manufacture of textiles 3,40% 1,85% -63,54% Manufacture of wearing apparel 8,27% 5,68% -53,97% Manufacture of leather and related products 1,41% 0,78% -62,67% Manufacture of wood and of products of wood and cork, except furniture; manufacture of articles of straw and plaiting materials 5,06% 5,26% -30,37% Manufacture of paper and paper products 1,67% 2,01% -19,10% Printing and reproduction of recorded media 7,62% 4,42% -61,08% Manufacture of coke and refined petroleum products 1,07% 1,40% -12,28% Manufacture of chemicals and chemical products 2,68% 2,74% -31,47% Manufacture of basic pharmaceutical products and pharmaceutical preparations 2,72% 3,89% -4,14% Manufacture of rubber and plastic products 2,70% 2,96% -26,39% Manufacture of other non-metallic mineral products 6,49% 5,82% -39,88% Manufacture of basic metals 3,88% 5,29% -8,70% Manufacture of fabricated metal products, except machinery and equipment 9,79% 10,04% -31,23% Manufacture of computer, electronic and optical products 1,11% 0,59% -64,41% Manufacture of electrical equipment 2,38% 2,10% -40,94% Manufacture of machinery and equipment n.e.c. 2,48% 1,93% -47,73% Manufacture of motor vehicles, trailers and semi-trailers 0,45% 0,73% 8,33% Manufacture of other transport equipment 2,46% 1,96% -46,56% Manufacture of furniture 6,79% 5,29% -47,79% Other manufacturing 2,79% 2,40% -42,28% Repair and installation of machinery and equipment 2,36% 2,52% -28,57% Total Manufacturing 1,0 1,0-32,92% From Table 2 we can conclude that the highest job destruction in manufacturing sectors was in the textiles and wearing apparel (58,5%) and in the manufacture of computer, electronic and optical products (64,4%). In the textiles industry, companies left the country or decreased their operations purposely due to globalized competition. The manufacture of motor vehicles and trailers showed an increase in employment (8,3%) while pharmaceuticals showed only a 4,1% decrease. Food products are also one of the few sectors that hold job positions in the crisis with a 8,44% decline (from 32,9% average for all the manufacturing

5 sector). Thus one may conclude that the impact of economic crisis has, indeed, affected differently employment in manufacturing sectors and in some cases have even positive a effect on employment. The paper is organized as follows. In section 2, the theoretical background and empirical findings are briefly introduced. Section 3, provides information on the sample and describes the data/variables used with the hypothesis testing. Section 4, presents and discusses the regression results and section 5, concludes and suggests policy measures implied by the findings of the study. 2. Theory and literature review In the theoretical background, there are various models for firm growth (Evans, 1987b; Variyam and. Kraybill, 1992). In 1931 Gibrat presented the Law of Proportional Effect. The law states that the growth of firms is proportional to their size, and growth occurs at the same growth rate regardless of their initial size. Early studies support Gibrat's law (Hart and Prais, 1956), but later studies do not. It should be noted that Gibrat's law fails to hold for small firms (Hart and Oulton, 1996, Audretsch et al., 1999), where empirical results show that growth is inversely related to size. The neo-classical view of the firm states that profits are a necessary condition for growth and determine the rate of growth. The higher the retention rate, the higher the growth rate of the firm, and the higher the profitability of the firm the higher the growth rate (g), according to the equation: g = (retention rate) x (return on assets) Equation (1) A comprehensive theory of the firm must be able to explain not only the incentive for firms to expand their horizontal boundaries, but also why firms within the same industry grow to different sizes and why for some firms growth is negative. The economies of scale and the stage in the life cycle of a firm do not explain the varying growth performance of individual firms. The competency approach theory places great emphasis on the entrepreneurial ability of the firm s senior management to perceive new productive opportunities and to utilize the firm s accumulated knowledge to exploit them (Rickard and Moger, 2006). Combining economies of scale with the perfect market assumption of a uniform price leads to the widely held conclusion that the larger manufacturers have lower costs and therefore greater profits. Thus, larger manufacturers will have a greater profit incentive to

6 expand. Early empirical evidence on employment growth showed that large firms are the major contributors of net new jobs in USA (Ijiri and Simon, 1964). According to Scumpeter s creative destruction theory, small firms that apply new technology, gain market share from the large sized ones. According to Jovanovic's (1982) life-style model, managerial efficiency and learning by doing are the key factors for firm growth. Jovanovic also showed that young firms grow faster than older ones and since young firms are usually small, this confirms the negative correlation between firm size and growth. Many empirical studies have found that small firms grow faster than the larger ones (Dunne and Hughes, 1994) and that growth declines with age (Evans, 1987). Up to middle 1970s, mass production predominated with uniform products. However, changes in consumer products, favored flexible firms which could adjust to changes. Many large firms with high fixed costs were not able to survive. On the contrary, small and medium sized firms (SMEs), being more flexible and with lower costs, salaries and wages, were more able to meet changes in demand, grow and create new jobs. Furthermore, rapid development of technology provided small firms with low cost computers, allowing for adjustment to change. Mismanagement, limited access to financing and information and lack or limited R&D, were responsible for job destruction in SMEs. Pakes and Ericson (1998) presented also a model on firm growth based on active learning and R & D activities, which was verified by empirical data on a panel of Wisconsin firms in Heshmati, (2001) from Sweden and Hohti, (2000) from Finland suggests that employment creation and destruction are negatively related to firm size. Broesma and Gautier (1997) for Dutch manufacturing firms and Klette and Mathiassen (1996) for Norwegian manufacturing firms agree to that, finding also negative relation with age. On the contrary, Wagner (1995b) found that there is no dramatic job generation by small firms in West Germany. Davis, Haltiwanger and Schuh (1993) claim that, it is large and not small firms that account for the bulk of job creation and destruction. The empirical literature, though, indicates that firm characteristics besides size and age, may play important role in the growth of firms. These characteristics are capital structure (Lang et al., 1996), research and development (Hall, 1987), human capital and export activities (Liu et al., 1999).

7 The growth of a firm is directly connected to employment growth through job creation and job destruction. Job destruction occurs either because firms go out of business or because they reduce their workforce. In general, closing establishments represent a small share of total employment (Lee and Rudick, 2006). It is job losses at continuing business that play a more important role in aggregate employment changes. An increase in the job destruction rate in the manufacturing sector does not necessarily suggest that the economy has been less competitive. This might be the result of creative destruction with workers placed from old jobs and less efficient firms to jobs that better fit the needs of the economy. This is a natural and necessary step to economic growth making the economy more competitive in the long run. In the case of Greece, the job reshuffling is basically among manufacturing and service firms and in the manufacturing sector, from labor intensive to new technology and heavy industry firms (Voulgaris, Papadogonas and Agiomirgianakis, 2005). Exports are an indication of competitiveness in a firm and a determinant of growth. R&D expenditures are perceived as an indicator of innovation by researchers (Wakelin, 1998; Guan J. and N. Ma, 2003). Therefore, both must have an impact on the growth of the firm and the net job creation. However, the level of the exchange rate and its volatility will certainly affect export performance in a firm and consequently its growth. For Greece, there are studies on job creation and job destruction such as: Voulgaris, Papadogonas and Agiomirianiakis (2005), examining job construction and destruction patterns in the Greek manufacturing sector for the period , just before Greece's entry to the European Monetary Union (EMU). The variables found as significant determinants to employment growth are firm size, age, profitability, sales growth, reliance on debt and investment in new fixed assets. Agiomirianakis, Voulgaris and Papadogonas (2004), examining financial factors affecting profitability and employment growth in the Greek manufacturing and Voulgaris, Asteriou, Agiomirgianakis (2003) analyzing factors affecting small manufacturing firm growth. Liargovas and K. Scandalidis (2008) has analyzed the profitability and employment growth of SMEs in Greece, while Fotopoulos et al. (2007), investigated manufacturing employment growth across Greek regions, a regional and not a firm level analysis. The above empirical analysis was based on old data ( ). However, the new economic developments with the prevailing worldwide depressionary economic conditions and the strong competitiveness

8 arising from globalization, plus the severe economic crisis in Greece, have changed the behavior of employment structure and the factors affecting it. This study aims to fill this gap. 3. Data and Descriptive Statistics The research is based on panel data, covering the period broken down in sub-periods, and The sample includes all private firms of corporate forms (societés anonymes and limited liability companies), which existed through all years of the study, while sole proprietorships and partnerships are excluded from all manufacturing sectors. As a result, the number of firms was 1397 in our database. All firm level data have been obtained from the ICAP Group, S.A., a private research company which collects balance sheet data for SA and Ltd companies in Greece, together with their employment, establishment date, location and ownership status. The breakdown of sample is as shown in Table 3: Table 3. Breakdown of sample Sector Code Number of Firms Sector Description MANUFACTURE OF FOOD PRODUCTS AND BEVERAGES 16 2 MANUFACTURE OF TOBACCO PRODUCTS MANUFACTURE OF TEXTILES MANUFACTURE OF WEARING APPAREL; DRESSING AND DYEING OF FUR TANNING AND DRESSING OF LEATHER; MANUFACTURE LUGGAGE, HANDBAGS, SADDLERY, HARNESS AND FOOT MANUFACTURE OF WOOD AND OF PRODUCTS OF WOOD AND CORK, EXCEPT FURNITURE; MANUFACTURE OF ARTICLES OF STRAW AND PLAITING MATERIALS MANUFACTURE OF PULP, PAPER AND PAPER PRODUCTS PUBLISHING, PRINTING AND REPRODUCTION OF RECORDED MEDIA MANUFACTURE OF COKE, REFINED PETROLEUM PRODUCTS AND NUCLEAR FUEL MANUFACTURE OF CHEMICAL AND CHEMICAL PRODUCTS MANUFACTURE OF RUBBER AND PLASTIC PRODUCTS MANUFACTURE OF OTHER NON-METALLIC MINERAL PRODUCTS MANUFACTURE OF BASIC METALS MANUFACTURE OF FABRICATED METAL PRODUCTS, EXCEPT MACHINERY AND EQUIPMENT MANUFACTURE OF MACHINERY AND EQUIPMENT N.E.C MANUFACTURE OF ELECTRICAL MACHINERY AND APPARATUS N.E.C. MANUFACTURE OF RADIO, TELEVISION AND COMMUNICATION EQUIPMENT AND APPARATUS

9 33 1 MANUFACTURE OF MEDICAL, PRECISION AND OPTICAL INSTRUMENTS, WATCHES AND CLOCKS MANUFACTURE OF MOTOR VEHICLES, TRAILERS AND SEMI- TRAILERS MANUFACTURE OF OTHER TRANSPORT EQUIPMENT MANUFACTURE OF FURNITURE; MANUFACTURING N.E.C 1397 TOTAL The variables were selected based on literature and theory, as explained in section 2. The dependent variable is change in employment between 2003 and For model (a) employment is taken that of the base year 2003 and for model (b) year Employment is measured in terms of number of employees for each firm. The variables included in the model and expected relation with the dependent variable are shown in Table 4. Table 4. Variables and Hypothesis testing Variables Change in employment between Description of variables Dependent Variable Expected correlation sign Independent Variables Crisis Dummy Value 1 after the crisis and value of 0 before the crisis (-) Age Year of establishment year 2003 and 2007 (-) Market Share at start year sales i Salesofthesector (-) Market Share Growth % change in market share between the years t +4 t (+) Investment Change in Net Fixed Assets from year t-1 to year t (+) Sales/Current Assets at start year Current Assets turnover (+) Total Debt / Total Leverage at year t Liabilities (-) Exports at year t exports (+) ROA at year t Net Profit/Total Assets (+) Percentage growth in ROA Growth ROA between the years t +4 t (+) Labor Productivity at year t Sales / no of employees (+)

10 Labor Productivity Growth Change in labor productivity between the years t +4 t (-) Firms were classified into small, medium and large, based on the number of employees (1-49 small, medium, and > 250 large), attempting to determine differences in their performance before and after the economic crisis in Greece, based on the variables used in the models. Descriptive statistics Table 5. Descriptive statistics period All firms 2003 (n = 1397) Descriptive Statistics Period Small firms 2003 (n = 1001) Medium firms 2003 (n = 312) Large firms 2003 (n = 84) Variables Mean Mean Mean Mean small, medium Probabilities small, large mediumlarge AGE 23,09 19,43 31,27 35,35 0, , ,00000*** EMPLOYMENT 74,86 19,46 107,30 600,10 0,00000*** 0,00000*** 0,00000*** PRODUCTIVITY , ,000000*** 0,00000*** MARKET SHARE 0,07 0,03 0,11 0,28 0,00000*** 0, , ROA 0,05 0,05 0,05 0,07 0, , , LEVERAGE 0,55 0,54 0,58 0,57 0,011234** 0, , INVESTMENT 0,70 0,70 0,74 0,47 0, , , PRODUCTIVITY GROWTH 0,79 0,72 1,11 0,39 0, , , MARKET SHARE GROWTH 0,26 0,22 0,49-0,04 0, , , ROA GROWTH -2,16-2,64-0,90-1,30 0, , , SALES/CURRENT ASSETS 2,29 2,27 2,37 2,31 0, ,023619** 0,023174** Exports 0,69 0,62 0,86 0,96 0,00000*** 0, , EMPLOYMENT GROWTH 0,13 0,18 0,02-0,01 0, , , * Significant at the 10% level (two-tailed test), ** Significant at the 5% level (two-tailed test), *** Significant at the 1% level, (two-tailed test), t ratios are in parentheses. Standard errors are White Heteroscedasticity consistent Table 6. Descriptive statistics period All firms 2003 (n = 1397) Descriptive statistics Period Small firms 2003 (n = 1001) Medium firms 2003 (n = 312) Large firms 2003 (n = 84) Variables Mean Mean Mean Mean small, medium Probabilities small, large mediumlarge

11 AGE 27,14 23,67 34,57 38,81 0, ,00000*** 0,53648*** EMPLOYMENT 75,60 19,61 109,54 594,43 0,00000*** 0,00000*** 0,00000*** PRODUCTIVITY , ,02878** 0,01877** MARKET SHARE 0,06 0,03 0,09 0,28 0,00000*** 0,00000*** 0,00000*** ROA 0,04 0,04 0,03 0,05 0, , ,11456 LEVERAGE 0,58 0,57 0,60 0,62 0, , ,67153 INVESTMENT 0,20 0,23 0,13-0,03 0,00744*** 0,00000*** 0,00067*** PRODUCTIVITY GROWTH 0,47 0,03 0,11 0,68 0, , ,93386 MARKET SHARE GROWTH 0,27 0,32 0,09 0,28 0, , ,57040 ROA GROWTH -0,80-5,72 14,45 1,16 0, ,00162*** 0,44317 SALES/CURRENT ASSETS 1,89 1,79 2,11 2,10 0,03014** 0, ,94959 Exports 0,70 0,62 0,86 0,95 0,00000*** 0,00000*** 0,00173*** EMPLOYMENT GROWTH -0,01 0,03-0,07-0,15 0,04157** 0,00019*** 0,08741 * Significant at the 10% level (two-tailed test), ** Significant at the 5% level (two-tailed test), *** Significant at the 1% level, (two-tailed test), t ratios are in parentheses. Standard errors are White Heteroscedasticity consistent From the descriptive statistics we notice that Large firms are the older firms both before and after the crisis Large firms are the most productive and profitable firms before and after the crisis Large firms make the lowest net investments due to lack of domestic demand Productivity growth was the highest in the small firms before crisis and in large firms after the crisis, since large firms were the ones surviving the crisis. Market share growth was the highest in small firms and in large firms after the crisis ROA growth was the highest in medium sized firms after crisis. Exports were highest in large firms benefited by economies of scale since competition in the export markets is basically on pricing. Employment growth was the highest in small firms in both the pro and after crisis period. 4. Methodology and Results We used Panel EGLS method with diagonal correction of standard errors for heteroscedasticity and autocorrelation (according to the White methodology) and crosssection weights. There is no indication that the data structure is characterized by period specific heteroskedasticity, contemporaneous covariances, and between-period covariances. The model was estimated only for the firms that existed in both periods i.e and

12 We excluded from the analysis firms that closed or were established during those periods. As a result, the number of firms decreased to 1397 in our database. As explained above, the dependent variable is change in employment For model (a) employment is taken that of the base year For model (b), employment used is that of year Table 5. Results for all years models Variables Model (a) Model (b) Coefficient t-statistic Coefficient t-statistic Crisis Dummy -0,0950*** 8,10-0,1063*** 9,32 Age 0,0001*** 4,27 0,0003 0,37 Market Share ,2509*** 7,24 Market Share Growth 0,1406*** 3, Investment 0,0452*** 7,59 0,0413*** 7,94 Sales/Current Assets 0,0129*** 6,89 0,0104*** 6,24 Leverage -0,1899*** 8,61-0,3245*** 8,78 Exports 0,0153*** 3,49 0,0293*** 5,34 ROA ,5064*** 7,84 ROA Growth 0,0001*** 9, Labor Productivity - - 0,0001*** 9,02 Labor Productivity Growth -0,0459*** 7,39 Adj. R-squared 0,669 0,568 * Significant at the 10% level (two-tailed test), ** Significant at the 5% level (two-tailed test), *** Significant at the 1% level, (two-tailed test), t ratios are in parentheses. Standard errors are White Heteroscedasticity consistent The alternative to employment growth, as dependent variable, would be the net job creation, taking into consideration the closing down and the entry of new firms. Since the information on this was hard to find, we used the employment growth. The independent variables are the ones showing in the previous table, plus a number of dummy variables to control for heterogeneity among firms and industrial sectors. The findings indicate that age is positively correlated to employment growth and significant at the 5% level, against theory and empirical findings abroad as well as against findings in previous study of the authors for the before 2000 period in Greece. The reason for this is the crisis effect, i.e only older experienced firms with reputation effects, were able to hold jobs after 2008 (Jovanovic s theory).

13 Table 6. Results of EGLS model for the pre crisis period ( ) (a) (b) Coefficient t-statistic Coefficient t-statistic Age -0,0001 1,2 0,0003 0,93 Market Share ,0255 1,48 Market Share Growth 0,9422*** 6, Investment 0,0165*** 2,48 0,0778 1,38 Sales/Current Assets 0,0150 1,01 0,0128 0,97 Leverage -0,2524** 2,05-0,4642** 2,18 X -0,1271** 2,17 0,0052 1,05 ROA ,3200 1,45 ROA Growth 0,0003** 2, Labor Productivity - - 0,0001 0,27 Labor Productivity Growth -0,6838*** 5,43 Adj. R-squared 0,842 0,425 * Significant at the 10% level (two-tailed test), ** Significant at the 5% level (two-tailed test), *** Significant at the 1% level, (two-tailed test), t ratios are in parentheses. Standard errors are White Heteroscedasticity consistent Table 7. Results of EGLS model for the post crisis period ( ) (a) (b) Coefficient t-statistic Coefficient t-statistic Age 0,0001** 2,68 0,0001 0,44 Market Share ,5374*** 3,46 Market Share Growth 0,0155 1, Investment 0,1614*** 3,25 0,1477*** 6,38 Sales/Current Assets 0,0291** 1,99 0,0091 1,03 Leverage -0,0007 0,90-0,0888 1,22 X 0,0207*** 2,24 0,0226 1,38 ROA ,1053* 1,78 ROA Growth 0,0007** 2, Labor Productivity - - 0,0001*** 7,78 Labor Productivity Growth -0,0032*** 2,89 Adj. R-squared 0,571 0,332 * Significant at the 10% level (two-tailed test), ** Significant at the 5% level (two-tailed test), *** Significant at the 1% level, (two-tailed test), t ratios are in parentheses. Standard errors are White Heteroscedasticity consistent

14 In Tables 6&7 we see that from the regression models of the before and after the crisis periods, before crisis, young firms are the job creators. It is important to notice that this changes in the after crisis period. If we assume that usually older firms are medium to large size, this finding is supported by descriptive statistics, where ROA growth is higher for medium and large firms. Market share, used as a proxy for size, is negatively correlated with employment growth. This indicates that smaller firms create jobs, as explained by theory and previous empirical findings, inside and outside the country 3. Market share growth shows that firms that increase their market share create new jobs, as expected. Profitability growth (ROA), indicates that firms that are able to invest their funds gaining steadily high returns have capable management which helps them grow and create job positions even in crisis conditions. Exports do not create jobs before crisis, while they become important determinants of employment growth after the crisis. Looking at the descriptive statistics, we can see that decreased domestic demand has turned Greek firms to exporting. ROA came out with a negative correlation to employment growth, implying that profitable firms during crisis in Greece are firms that enjoy monopoly market conditions and do not strive to grow and create new jobs. Management is not very active and disciplined and do not act to the favor of stockholders. New investments in net fixed assets, used as proxy for new technology application, came out with positive correlation. This agrees with theory and previous findings for Greece (Voulgaris et al, 2005), as well as other studies abroad. Efficiency, measured as Sales/Current assets, a very important indicator for manufacturing firms, shows that firms that keep low levels of receivables and inventories, show managerial capabilities that enable them to be profitable, viable and create or keep their job positions. Leverage is negatively correlated, suggesting that large amounts of debt (usu. STD), create financial problems in Greek firms, encumbering them from keeping or creating new jobs. Labor productivity helps firms to grow and create new jobs, as expected. 3 See e.g. Oberhofer H. and Vincelette G. (2013) stating that at the firm level, small and younger surviving (including start-ups) were the most important contributors to job creation in the EU11 ; also, Ibsen R. and Westergaard-Nielsen N. (2011) claim that young firms are much more likely to contribute to a positive (employment) growth.

15 However, firms that enjoy labor productivity growth can exhibit low or negative employment growth, supported by the new Greek labor law. Exports increase sales and production activity, creating new jobs, only after the crisis, substituting the decrease of demand in the domestic market. Before crisis Greek firms were relying in the domestic market for sales and profits (therefore, the negative correlation). 5. Conclusions and Policy Implications Economic crisis has affected severely employment growth in the Greek manufacturing industry and has changed the determinants of job creation in the Greek firms. The most important finding and contribution of this study, is that after the crisis: 1. Older firms are the major job creators based on experience and reputation effects. This is opposed to findings of previous research (Voulgaris et al., 2005 and Agiomirgianakis et al.,2006) covering time periods 10 years ago. 2. Exports are critical determinants of employment growth (new finding). 3. New investment in fixed assets, used as a proxy for new technology application and innovation, play significant role in job creation. Combined with descriptive statistics, we can see that Net Fixed Assets Investments are higher for small firms, indicating use of new technology. This enables small firms to increase their market share (Schumpeter s theory). 4. Small firms continue to be the leaders in job creation Profitability is negatively correlated to employment growth. This is a new finding of the study (vs. previous studies) and can be explained by the monopoly conditions that prevailed after the crisis. This result is supported by the negative correlation of the labor productivity and growth 6. Large size firms are the most profitable with the lowest employment growth. Therefore, large firms are the major job destructors this is in line with Acquisti A. and Lehmann H. (2000). 7. Efficiency in the use of working capital assets, market share and productivity growth affect positively firm employment 4 As noted by Hijzen, A et al. (2010) small firms account for about 65% of jobs created and 45% of jobs destroyed.

16 Based on our findings, we would suggest a number of policy implications that Greek policy makers could adopt in order to support employment in the Greek manufacture: a) The Greek state should support older experienced firms, preferably of small and medium size, through subsidies, b) The adoption of new technologies and innovation should be encouraged by means of subsidies and tax reductions or by cutting the red tape, c) Steps undertaken by firms towards opening up new markets abroad for their products should be supported by governmental exports grants and advertised as examples of good practice and entrepreneur s adaptation to conditions of economic crisis. d) On the contrary, large firms should not be supported in sustaining employment as are the major job destructors. e) On the other hand, the food and beverages sectors, as well as, pharmaceuticals and transportation equipment are the sectors least affected by the economic crisis in job creation and thus a direct favorable discretionary policy may not be required. Concluding our analysis, we suggest that discretionary microeconomic policy measures in favour of small-medium sized firms that have a clear exporting character and apply innovative technologies/activities, should be adopted, in fighting large unemployment in Greece. These policy measures could take the form of tax reductions, investment subsidies, export grants, cutting the red tape and elevating examples of good practice and entrepreneur s adaptation to conditions of economic crisis.

17 References Agiomirgianakis G., Voulgaris F. and T. Papadogonas (2006) Financial Factors affecting profitability and employment growth: the case of Greek manufacturing, Int. J. of Financial Services Management, Vol. 1, Nos. 2/3, Acquisti A. and Lehmann H. (2000) Job Creation and Job Destruction in Russia:Some Preliminary Evidence from Enterprise-level Data Trinity Economic Technical Paper, 1/00, Audretsch, D., E. Santarelli and M. Vivarelli, (1999), "Start-up Size and Industrial Dynamics: Some Evidence from Italian Manufacturing", International Journal of Industrial Organization, 17, Audretsch, D. B., (1995a), "Innovation and Industry Evolution", Cambridge: MIT Press. Broersma, L. and P. Gautier, (1997), "Job Creation and Job Destruction by Small Firms: An Empirical Investigation for the Dutch Manufacturing Sector", Small Business Economics, 9, Davis, S. J., J. Haltiwanger and S. Schuh, (1993) "Small Business and Job Creation: Dissecting the Myth and Reassessing the Facts", Working paper No. 4492, Cambridge, MA.: National Bureau of Economic Research. Dunne, P. and A. Hughes, (1994), "Age, Size, Growth and Survival: U.K. Companies in the 1980s", Journal of Industrial Economics, Vol.42, Evans, D. S., (1987a), "The Relationship between Firm Growth, Size and Age: Estimates for 100 Manufacturing Industries", Journal of Industrial Economics, 35, Evans, D. S., (1987b), "Tests of Alternative Theories of Firm Growth", Journal of Political Economy, 95(4), Fotopoulos G., Kallioras D. and G. Petrakos, (2007), Spatial Variations of Greek Manufacturing Employment Growth: The effects of Specialization and International Trade Discussion Paper series, 13(1):1-22, University of Thessaly, Greece. Guan J. and N. Ma (2003) Innovative capability and export performance of Chinese firms Technovation Volume 23, Issue 9, September 2003, Pages Hall, B. H. (1987), "The Relationship Between Firm Size and Firm Growth in the U.S. Manufacturing Sector", Journal of Industrial Economics 35, (June), Hart, P. and N. Oulton, (1996), "Growth and Size of Firms", Economic Journal, 106, Heshmati, A., (2001), "On the Growth of Micro and Small Firms: Evidence from Sweden", Small Business Economics, Vol. 17, Hijzen, A.; Upward R; and Peter W. Wright (2010) Job Creation, Job Destruction and the Role of Small Firms: Firm-Level Evidence for the UK Oxford Bulletin of Economics And Statistics, 72, 5 Hohti, S., (2000), "Job Flows and Job Quality by Establishment Size in the Finnish Manufacturing Sector ", Small Business Economics, Vol. 15, pp Ibsen R. and Westergaard-Nielsen N. (2011) Job Creation by Firms in Denmark, IZA Discussion Paper No January 2011 Ijiri, Y. and H. Simon, (1964), "Business Growth and Firm Size", American Economic Review, Vol. 54 (March), pp Jovanovic, B., (1982), "Selection and Evolution of Industry", Econometrica, 50, Klette, T. and A. Mathiassen, (1996), "Job Creation, Job Destruction and Plant Turnover in Norwegian Manufacturing", Annales d' Economie et de Statistique, 41/42,

18 Lang, L., E. Ofek and R. M. Stulz, (1996), "Leverage, Investment, and Firm Growth", Journal of Financial Economics 40, Oberhofer H. and Vincelette G. (2013), Determinants of Job Creation in Eleven New EU Member States Evidence from Firm Level Data, The World Bank, Europe and Central Asia Region Poverty Reduction and Economic Management Department, July 2013 Liargovas P. and K. Scandalidis (2008) Factors Affecting Firms Financial Performance: The Case of Greece No 12, Working Papers from University of Peloponnese, Department of Economics. Liu, J.-T., M.-W. Tsou and J. Hammitt, (1999), "Do Small Plants Grow Faster; Evidence from the Taiwan Electronics Industry", Economics Letters 65, Pakes, A. and R. Ericson, (1998), "Empirical Implications of Alternative Models of Firm Dynamics", Journal of Economic Theory, 79, Pitelis C. and N. Antonakis (2003) Manufacturing and Competitiveness: the case of Greece Journal of Economic Studies, Vol. 30 No. 5, pp Rickards T. and S. Moger (2006) Creative Leaders: A Decade of Contributions from Creativity and Innovation Creativity and Innovation Management Volume 15, Issue 1, pages Variyam, J. N. and D. S. Kraybill, (1992), "Empirical Evidence on Determinants of Firm Growth", Economics Letters, 38, Voulgaris, F., D. Asteriou and G. Agiomirianakis (2003), The determinants of small firm growth in the Greek manufacturing sector, Journal of Economic Integration. 18(4), Voulgaris F., Papadogonas T. and G. Agiomirianakis (2005) Job creation and job destruction in Greek manufacturing Review of Development Economics, 0(2), 289- Wagner, J., (1995), "Firm Size and Job Creation in Germany", Small Business Economics, 7, , (1994), "Small Firm Entry in Manufacturing Industries: Lower saxony, ", Small Business Economics 6 (3), Wakelin, K. (2001), Productivity growth and R&D expenditure in U.K. manufacturing firms", Research Policy, 30,