<?xml version="1.0" encoding="UTF-8"?><!DOCTYPE article  PUBLIC "-//NLM//DTD Journal Publishing DTD v3.0 20080202//EN" "http://dtd.nlm.nih.gov/publishing/3.0/journalpublishing3.dtd"><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" dtd-version="3.0" xml:lang="en" article-type="research article"><front><journal-meta><journal-id journal-id-type="publisher-id">TEL</journal-id><journal-title-group><journal-title>Theoretical Economics Letters</journal-title></journal-title-group><issn pub-type="epub">2162-2078</issn><publisher><publisher-name>Scientific Research Publishing</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.4236/tel.2016.64083</article-id><article-id pub-id-type="publisher-id">TEL-69993</article-id><article-categories><subj-group subj-group-type="heading"><subject>Articles</subject></subj-group><subj-group subj-group-type="Discipline-v2"><subject>Business&amp;Economics</subject></subj-group></article-categories><title-group><article-title>
 
 
  Manufacturing Firms’ Performance and Productivity: Evidence from North and South European, Scandinavian and Balkan Countries
 
</article-title></title-group><contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Christos</surname><given-names>Lemonakis</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Konstantinos</surname><given-names>Vassakis</given-names></name><xref ref-type="aff" rid="aff2"><sup>2</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Alexandros</surname><given-names>Garefalakis</given-names></name><xref ref-type="aff" rid="aff3"><sup>3</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Xanthi</surname><given-names>Partalidou</given-names></name><xref ref-type="aff" rid="aff4"><sup>4</sup></xref></contrib></contrib-group><aff id="aff3"><addr-line>Department of Accounting and Finance, Technological Educational Institute of Crete, Heraklion, Greece</addr-line></aff><aff id="aff2"><addr-line>Department of Science, Technological Educational Institute of Crete, Heraklion, Greece</addr-line></aff><aff id="aff1"><addr-line>School of Business Administration, MBA Program, Neapolis University, Pafos, Cyprus</addr-line></aff><aff id="aff4"><addr-line>Department of Agricultural Development, Democritus University of Thrace, Orestiada, Greece</addr-line></aff><pub-date pub-type="epub"><day>19</day><month>07</month><year>2016</year></pub-date><volume>06</volume><issue>04</issue><fpage>789</fpage><lpage>797</lpage><history><date date-type="received"><day>25</day>	<month>July</month>	<year>2016</year></date><date date-type="rev-recd"><day>accepted</day>	<month>21</month>	<year>August</year>	</date><date date-type="accepted"><day>24</day>	<month>August</month>	<year>2016</year></date></history><permissions><copyright-statement>&#169; Copyright  2014 by authors and Scientific Research Publishing Inc. </copyright-statement><copyright-year>2014</copyright-year><license><license-p>This work is licensed under the Creative Commons Attribution International License (CC BY). http://creativecommons.org/licenses/by/4.0/</license-p></license></permissions><abstract><p>
 
 
  The purpose of the study is to analyze and compare the financial performance of manufacturing firms of Central and South European, Scandinavian and Balkan countries. In addition, the impact of firm’s productivity on country’s export intensity, foreign direct investments, R&amp;D activity and 
  financing costs is examined. This is the first comparative study making an inter-country, interre
  gional and inter-manufacturing sector comparison of the financial performance of manufacturing firms in European, Scandinavian and Balkan regions through selected countries. This research at
  tempts to investigate the relation 
  of macro variables, such as country
   export intensity, FDI and R&amp;D on the competitiveness of the manufacturing firms in those countries measured on the firm level. In order to access the factors that affect the competitiveness of the manufacturing firms in each one of the 15 countries of the sample, we run 15 Tobit (truncated) models, using balanced panel data for the period 2008-2011.
 
</p></abstract><kwd-group><kwd>Manufacturing</kwd><kwd> Performance</kwd><kwd> FDI</kwd><kwd> R&amp;D</kwd><kwd> Competitiveness</kwd><kwd> Sales per Employee</kwd></kwd-group></article-meta></front><body><sec id="s1"><title>1. Introduction</title><p>The competitiveness of the economies of Balkan countries represents a strategic European interest. Well- functioning market economies that resistant to global competitive pressures contributing to the political stabilization of the Western Balkan region as well as to growth and jobs for Europe, which is the EU’s main policy objective for the years to come. Foreign direct investment (FDI) inflows help sustain economic growth and generate employment in the formal sector, promote exports, rebalance growing trade deficits and maintain the process of economic reconstruction.</p><p>This paper makes an inter-country as well as inter-regional and inter-manufacturing sector comparison of the financial performance of manufacturing firms in European, Scandinavian and Balkan regions through selected countries. To the best of our knowledge, there is not such a comparative study so far.</p><p>Furthermore, the research attempts to investigate the relation of macro variables, such as country export intensity, FDI and R&amp;D on the competitiveness of the manufacturing firms in those countries measured on the firm level. In current literature, most of the published studies examine the bivariate relationship, theoretically or empirically, between economic growth and exports, economic growth and foreign direct investments or exports and foreign direct investments.</p><p>The study is structured as follows: the next section presents relevant literature, while section 3 highlights the methodology as well as the model approach of the study. In section 4, the empirical results of the study are presented and discussed. Section 5 summarizes the empirical findings and draws the policy implications of the study.</p></sec><sec id="s2"><title>2. Literature Review</title><p>The inter-country as well as inter-region comparisons of firms’ financial characteristics have concentrated great interest in finance. Comparing the financial performance of diverse groups of firms, [<xref ref-type="bibr" rid="scirp.69993-ref1">1</xref>] and [<xref ref-type="bibr" rid="scirp.69993-ref2">2</xref>] predict the financial performance of healthy and no-healthy firms. Reference [<xref ref-type="bibr" rid="scirp.69993-ref3">3</xref>] compares the overall financial characteristics of U.S. and Japanese manufacturing firms with data from 28 different industries. Reference [<xref ref-type="bibr" rid="scirp.69993-ref4">4</xref>] finds significant differences between the financial performance of U.S.A. and Canadian manufacturing firms. Reference [<xref ref-type="bibr" rid="scirp.69993-ref5">5</xref>] compares U.S., E.U., and Japanese manufacturing firms and finds that their financial performances are significantly different. Reference [<xref ref-type="bibr" rid="scirp.69993-ref6">6</xref>] compares the financial performance of manufacturing firms within the E.U. and concludes that, despite economic integration, the differences between the financial performances of firms in different E.U. countries persist.</p><p>R&amp;D and innovation has recognized as key factor of firms’ productivity and income gains. In the majority of the empirical studies, economic growth is significantly correlated with foreign direct investments (FDI), exports and R&amp;D investments. FDI inflows can play a vital role in host countries due to the fact that it increases the supply of funds for domestic investments. Furthermore, FDI inflows not only can increase the export capacity of the host country but also encourage the creation of new jobs. In addition, foreign technology transfer through imported inputs and foreign investments lead on the success of the manufacturing sector [<xref ref-type="bibr" rid="scirp.69993-ref7">7</xref>] (Goldberg et al., 2010).</p><p>Reference [<xref ref-type="bibr" rid="scirp.69993-ref8">8</xref>] supports that there exists a triangular relationship among FDI, exports and economic growth. This means that FDI has both direct and indirect effects on economic growth through exports. Reference [<xref ref-type="bibr" rid="scirp.69993-ref9">9</xref>] examined the Granger causality relations among GDP, exports and FDI in Middle East and North Africa (MENA) countries and found that there are bidirectional causality relations among these variables. The technology and expertise (know-how) of multinational firms seems to play vital role for international knowledge transfer. Therefore, FDI lead to significant positive spillover effects on the labor productivity of domestic firms [<xref ref-type="bibr" rid="scirp.69993-ref10">10</xref>] .</p><p>Reference [<xref ref-type="bibr" rid="scirp.69993-ref11">11</xref>] investigated the relationship between exports, FDI of Greece over the period of 1960-2002. This study found that there is a long run relation and a causality relation between the examined variables. Reference [<xref ref-type="bibr" rid="scirp.69993-ref12">12</xref>] investigated the relationship among economic growth, exports and FDI for ten European countries over the period 1994-2008. Their study revealed that there is causality relation among FDI, exports and economic growth in four out of ten countries. Reference [<xref ref-type="bibr" rid="scirp.69993-ref13">13</xref>] examined the impact of substantial FDI inflows in producer service sectors on the total factor productivity of Chilean manufacturing firms and suggested that service FDI fostering innovation activities of manufacturing firms and offering opportunities for less competitive firms against industry leaders.</p><p>Many empirical studies examined the relationship between innovation-productivity and innovation-exporting activity. The majority of the studies highlight R&amp;D investments as a significant determinant of firm’s productivity [<xref ref-type="bibr" rid="scirp.69993-ref14">14</xref>] , while others conclude to the positive correlation between R&amp;D and firm exporting activity [<xref ref-type="bibr" rid="scirp.69993-ref15">15</xref>] . However, there is no clear research indicating the relationship between productivity, exports, R&amp;D and FDI at manufacturing firm-level data.</p><p>A debate in empirical studies about the impact of exports on productivity growth, using country or industry level data, exists [<xref ref-type="bibr" rid="scirp.69993-ref16">16</xref>] - [<xref ref-type="bibr" rid="scirp.69993-ref18">18</xref>] using data from 34 countries covering the time period 1995-2006, indicated that exporters are more productive than non-exporters, while exporting does not necessarily improve productivity. In that context, [<xref ref-type="bibr" rid="scirp.69993-ref19">19</xref>] concluded that US manufacturing exporting firms present higher productivity levels, but they have not find evidence that export activity affects productivity growth. Reference [<xref ref-type="bibr" rid="scirp.69993-ref20">20</xref>] using a data sample of UK small firms concluded that firms with exporting activity (regular, irregular and new exporters) have higher productivity measured with sales per worker than non-exporters.</p><p>The study investigates at first part the financial performance of manufacturing firms in North and South European, Scandinavian and Balkan Countries and compares them in terms of size, growth, profitability, productivity, liquidity and capital intensity. Through econometric modeling, we focus on the effect of country export intensity on firm level productivity, controlled for FDI, R&amp;D, labor productivity and cost of financing [<xref ref-type="bibr" rid="scirp.69993-ref21">21</xref>] .</p></sec><sec id="s3"><title>3. Methodology and Data</title><sec id="s3_1"><title>3.1. Data</title><p>The study covers the period 2008-2012, taking into account the post economic crisis effects. The data sample consists of 1159 firms from sixteen (16) countries: Austria, Belgium, Denmark, France, Germany, United Kingdom (North and Central Europe region), Italy, Portugal, Spain (Southern Europe region), Finland, Norway, Sweden, (Scandinavian region) Bulgaria, Lithuania, Montenegro and Greece (Balkan region). The dataset in this study appears for the first time in order to making an inter-country, inter-regional and inter-manufacturing sector comparison between the financial performance and profile manufacturing firms in European, Scandinavian and Balkan regions. The data were taken from the Datastream database (Tables 1-3).</p><table-wrap id="table1" ><label><xref ref-type="table" rid="table1">Table 1</xref></label><caption><title> Number of firms per country</title></caption><table><tbody><thead><tr><th align="center" valign="middle" >Country</th><th align="center" valign="middle" >Number of Firms</th><th align="center" valign="middle" >Percentage %</th></tr></thead><tr><td align="center" valign="middle" >Austria</td><td align="center" valign="middle" >41</td><td align="center" valign="middle" >3.54%</td></tr><tr><td align="center" valign="middle" >Belgium</td><td align="center" valign="middle" >47</td><td align="center" valign="middle" >4.06%</td></tr><tr><td align="center" valign="middle" >Bulgaria</td><td align="center" valign="middle" >7</td><td align="center" valign="middle" >0.60%</td></tr><tr><td align="center" valign="middle" >Denmark</td><td align="center" valign="middle" >17</td><td align="center" valign="middle" >1.47%</td></tr><tr><td align="center" valign="middle" >Finland</td><td align="center" valign="middle" >58</td><td align="center" valign="middle" >5.00%</td></tr><tr><td align="center" valign="middle" >France</td><td align="center" valign="middle" >181</td><td align="center" valign="middle" >15.62%</td></tr><tr><td align="center" valign="middle" >Germany</td><td align="center" valign="middle" >242</td><td align="center" valign="middle" >20.88%</td></tr><tr><td align="center" valign="middle" >Greece</td><td align="center" valign="middle" >88</td><td align="center" valign="middle" >7.59%</td></tr><tr><td align="center" valign="middle" >Italy</td><td align="center" valign="middle" >69</td><td align="center" valign="middle" >5.95%</td></tr><tr><td align="center" valign="middle" >Lithuania</td><td align="center" valign="middle" >21</td><td align="center" valign="middle" >1.81%</td></tr><tr><td align="center" valign="middle" >Montenegro</td><td align="center" valign="middle" >84</td><td align="center" valign="middle" >7.25%</td></tr><tr><td align="center" valign="middle" >Norway</td><td align="center" valign="middle" >28</td><td align="center" valign="middle" >2.42%</td></tr><tr><td align="center" valign="middle" >Portugal</td><td align="center" valign="middle" >20</td><td align="center" valign="middle" >1.73%</td></tr><tr><td align="center" valign="middle" >Spain</td><td align="center" valign="middle" >65</td><td align="center" valign="middle" >5.61%</td></tr><tr><td align="center" valign="middle" >Sweden</td><td align="center" valign="middle" >58</td><td align="center" valign="middle" >5.00%</td></tr><tr><td align="center" valign="middle" >United Kingdom</td><td align="center" valign="middle" >133</td><td align="center" valign="middle" >11.48%</td></tr><tr><td align="center" valign="middle" >Total number (16 Countries)</td><td align="center" valign="middle" >1.159</td><td align="center" valign="middle" >100.00%</td></tr></tbody></table></table-wrap><table-wrap id="table2" ><label><xref ref-type="table" rid="table2">Table 2</xref></label><caption><title> Number of firms per country</title></caption><table><tbody><thead><tr><th align="center" valign="middle" >Regions</th><th align="center" valign="middle" >Countries</th><th align="center" valign="middle" >Number of Firms</th></tr></thead><tr><td align="center" valign="middle" >BALKANS</td><td align="center" valign="middle" >Bulgaria, Greece, Lithuania and Montenegro</td><td align="center" valign="middle" >200</td></tr><tr><td align="center" valign="middle" >EUROPEAN</td><td align="center" valign="middle" >Austria, Belgium, France, Germany, Italy, Portugal, Spain and United Kingdom</td><td align="center" valign="middle" >798</td></tr><tr><td align="center" valign="middle" >SCANDINAVIAN</td><td align="center" valign="middle" >Denmark, Finland, Norway and Sweden</td><td align="center" valign="middle" >161</td></tr><tr><td align="center" valign="middle" >Sum</td><td align="center" valign="middle" ></td><td align="center" valign="middle" >1159</td></tr></tbody></table></table-wrap><table-wrap id="table3" ><label><xref ref-type="table" rid="table3">Table 3</xref></label><caption><title> Number of firms per sector/region</title></caption><table><tbody><thead><tr><th align="center" valign="middle" >Sectors</th><th align="center" valign="middle" >BALKANS</th><th align="center" valign="middle" >EUROPEAN</th><th align="center" valign="middle" >SCANDINAVIAN</th><th align="center" valign="middle" >Number of Firms per Sector</th></tr></thead><tr><td align="center" valign="middle" >Automobiles and Parts</td><td align="center" valign="middle" >3</td><td align="center" valign="middle" >57</td><td align="center" valign="middle" >4</td><td align="center" valign="middle" >64</td></tr><tr><td align="center" valign="middle" >Beverages</td><td align="center" valign="middle" >14</td><td align="center" valign="middle" >59</td><td align="center" valign="middle" >4</td><td align="center" valign="middle" >77</td></tr><tr><td align="center" valign="middle" >Chemicals</td><td align="center" valign="middle" >9</td><td align="center" valign="middle" >78</td><td align="center" valign="middle" >5</td><td align="center" valign="middle" >92</td></tr><tr><td align="center" valign="middle" >Construction and Materials</td><td align="center" valign="middle" >60</td><td align="center" valign="middle" >118</td><td align="center" valign="middle" >21</td><td align="center" valign="middle" >199</td></tr><tr><td align="center" valign="middle" >Food Producers</td><td align="center" valign="middle" >56</td><td align="center" valign="middle" >89</td><td align="center" valign="middle" >19</td><td align="center" valign="middle" >164</td></tr><tr><td align="center" valign="middle" >Forestry and Paper</td><td align="center" valign="middle" >12</td><td align="center" valign="middle" >21</td><td align="center" valign="middle" >12</td><td align="center" valign="middle" >45</td></tr><tr><td align="center" valign="middle" >Industrial Engineering</td><td align="center" valign="middle" >12</td><td align="center" valign="middle" >133</td><td align="center" valign="middle" >31</td><td align="center" valign="middle" >176</td></tr><tr><td align="center" valign="middle" >Industrial Metals and Mining</td><td align="center" valign="middle" >23</td><td align="center" valign="middle" >36</td><td align="center" valign="middle" >10</td><td align="center" valign="middle" >69</td></tr><tr><td align="center" valign="middle" >Pharmaceuticals and Biotechnology</td><td align="center" valign="middle" >4</td><td align="center" valign="middle" >115</td><td align="center" valign="middle" >35</td><td align="center" valign="middle" >154</td></tr><tr><td align="center" valign="middle" >Technology Hardware and Equipment</td><td align="center" valign="middle" >7</td><td align="center" valign="middle" >92</td><td align="center" valign="middle" >20</td><td align="center" valign="middle" >119</td></tr><tr><td align="center" valign="middle" >Total Number</td><td align="center" valign="middle" >200</td><td align="center" valign="middle" >798</td><td align="center" valign="middle" >161</td><td align="center" valign="middle" >1159</td></tr></tbody></table></table-wrap></sec><sec id="s3_2"><title>3.2. Units</title><p>At first, t-test of means is used to check for differences and compare their performance. The variables are used in order to investigate the characteristics of firms in the examining regions:</p><p>・ Size (total assets, total assets growth),</p><p>・ Firm’s growth (sales growth, total assets growth),</p><p>・ Labor productivity (sales/no. of employees),</p><p>・ Profitability (gross profit margin, ROA, net profit margin) [<xref ref-type="bibr" rid="scirp.69993-ref22">22</xref>] ,</p><p>・ Change in machinery &amp; equipment,</p><p>・ Inventory turnover,</p><p>・ Capitalization (net fixed assets/total assets),</p><p>・ Leverage (long term debt/equity) [<xref ref-type="bibr" rid="scirp.69993-ref23">23</xref>] ,</p><p>・ Liquidity.</p><p>In order to access the factors that affect the competitiveness of the manufacturing firms in each one of the 15 countries of the sample, we run 15 Tobit (truncated) models, using balanced panel data for the period 2008-2011, after crisis.</p><p>The dependent variable used is a measure of productivity, sales per no of employees for each firm used as proxy for competitiveness, with independent variables macro variables: value of exports for each country, FDI and R&amp;D. More specifically, macro variables that are used are:</p><p>・ Export value index (2000 = 100): Export values are the current value of exports (f.o.b.) converted to Euros and expressed as a percentage of the average for the base period (2000).</p><p>・ Research and development expenditure (% of GDP): Gross domestic expenditure on scientific research and experimental development (R&amp;D) expressed as a percentage of Gross Domestic Product.</p><p>・ Foreign direct investment, net inflows (% of GDP): Foreign direct investment are the net inflows of investment to acquire a lasting management interest in an enterprise operating in an economy other than that of the investor divided by GDP.</p><p>From the previous (<xref ref-type="table" rid="table1">Table 1</xref>), it is observed that for the post crisis period, the most profitable sectors in terms of ROA are: pharmaceuticals, food &amp; beverages and Industrial Engineering sectors. The highest value of Total Assets Growth was shown in Pharmaceuticals, Industrial Engineering and Construction Materials sectors. The most highly levered are Automobiles, Beverages and Chemicals. All sectors show negative net fixed assets formation [<xref ref-type="bibr" rid="scirp.69993-ref24">24</xref>] . The most productive in terms of labor are forestry and paper, food products and automobiles (<xref ref-type="table" rid="table4">Table 4</xref>).</p><disp-formula id="scirp.69993-formula1"><label>. (1)</label><graphic position="anchor" xlink:href="http://html.scirp.org/file/17-1500945x6.png"  xlink:type="simple"/></disp-formula><p>Note that from <xref ref-type="table" rid="table2">Table 2</xref>, it is concluded that:</p><p>1) The highest sales growth was in Pharmaceuticals, Industrial Metals and Food industry,</p><table-wrap-group id="4"><label><xref ref-type="table" rid="table4">Table 4</xref></label><caption><title> Descriptive statistics by sector</title></caption><table-wrap id="4_1"><caption><title> (b)</title></caption><table><tbody><thead><tr><th align="center" valign="middle" >Sectors</th><th align="center" valign="middle" >Return on Assets (%)</th><th align="center" valign="middle" >Total Assets Growth (%)</th><th align="center" valign="middle" >Long Term Debt/Equity (%)</th><th align="center" valign="middle" >Change in Machinery &amp; Equipment (%)</th><th align="center" valign="middle" >Sales per Employee in Euros</th></tr></thead><tr><td align="center" valign="middle" >Automobiles and Parts</td><td align="center" valign="middle" >1.43</td><td align="center" valign="middle" >2.05</td><td align="center" valign="middle" >103.70</td><td align="center" valign="middle" >−6.45</td><td align="center" valign="middle" >741.65</td></tr><tr><td align="center" valign="middle" >Beverages</td><td align="center" valign="middle" >2.92</td><td align="center" valign="middle" >1.03</td><td align="center" valign="middle" >119.60</td><td align="center" valign="middle" >−4.25</td><td align="center" valign="middle" >387.06</td></tr><tr><td align="center" valign="middle" >Chemicals</td><td align="center" valign="middle" >0.31</td><td align="center" valign="middle" >1.34</td><td align="center" valign="middle" >90.58</td><td align="center" valign="middle" >−8.27</td><td align="center" valign="middle" >491.67</td></tr><tr><td align="center" valign="middle" >Construction and Materials</td><td align="center" valign="middle" >2.37</td><td align="center" valign="middle" >6.94</td><td align="center" valign="middle" >82.87</td><td align="center" valign="middle" >−5.23</td><td align="center" valign="middle" >367.07</td></tr><tr><td align="center" valign="middle" >Food Producers</td><td align="center" valign="middle" >3.04</td><td align="center" valign="middle" >3.77</td><td align="center" valign="middle" >84.09</td><td align="center" valign="middle" >−7.85</td><td align="center" valign="middle" >893.26</td></tr><tr><td align="center" valign="middle" >Forestry and Paper</td><td align="center" valign="middle" >2.85</td><td align="center" valign="middle" >−0.58</td><td align="center" valign="middle" >69.24</td><td align="center" valign="middle" >−4.09</td><td align="center" valign="middle" >2392.77</td></tr><tr><td align="center" valign="middle" >Industrial Engineering</td><td align="center" valign="middle" >4.04</td><td align="center" valign="middle" >11.55</td><td align="center" valign="middle" >49.00</td><td align="center" valign="middle" >−8.20</td><td align="center" valign="middle" >347.62</td></tr><tr><td align="center" valign="middle" >Industrial Metals and Mining</td><td align="center" valign="middle" >0.98</td><td align="center" valign="middle" >2.83</td><td align="center" valign="middle" >49.86</td><td align="center" valign="middle" >−11.06</td><td align="center" valign="middle" >619.63</td></tr><tr><td align="center" valign="middle" >Pharmaceuticals and Biotechnology</td><td align="center" valign="middle" >13.10</td><td align="center" valign="middle" >15.77</td><td align="center" valign="middle" >59.95</td><td align="center" valign="middle" >−8.09</td><td align="center" valign="middle" >543.23</td></tr><tr><td align="center" valign="middle" >Technology Hardware and Equipment</td><td align="center" valign="middle" >2.04</td><td align="center" valign="middle" >6.28</td><td align="center" valign="middle" >36.01</td><td align="center" valign="middle" >−2.84%</td><td align="center" valign="middle" >733.70</td></tr></tbody></table></table-wrap><table-wrap id="4_2"><caption><title></title></caption><table><tbody><thead><tr><th align="center" valign="middle" >Sectors</th><th align="center" valign="middle" >Liquidity</th><th align="center" valign="middle" >Sales Growth (%)</th><th align="center" valign="middle" >Net Fixed Assets/Total Assets (%)</th><th align="center" valign="middle" >Gross Profit Margin Growth (%)</th><th align="center" valign="middle" >Property, Plant, Equipment (PPE) Growth (%)</th></tr></thead><tr><td align="center" valign="middle" >Automobiles and Parts</td><td align="center" valign="middle" >1.04</td><td align="center" valign="middle" >6.35</td><td align="center" valign="middle" >25.15</td><td align="center" valign="middle" >9.68</td><td align="center" valign="middle" >5.41</td></tr><tr><td align="center" valign="middle" >Beverages</td><td align="center" valign="middle" >0.81</td><td align="center" valign="middle" >5.14</td><td align="center" valign="middle" >31.42</td><td align="center" valign="middle" >13.13</td><td align="center" valign="middle" >1.03</td></tr><tr><td align="center" valign="middle" >Chemicals</td><td align="center" valign="middle" >1.96</td><td align="center" valign="middle" >8.96</td><td align="center" valign="middle" >30.59</td><td align="center" valign="middle" >5.79</td><td align="center" valign="middle" >3.74</td></tr><tr><td align="center" valign="middle" >Construction and Materials</td><td align="center" valign="middle" >1.24</td><td align="center" valign="middle" >0.62</td><td align="center" valign="middle" >29.48</td><td align="center" valign="middle" >1.57</td><td align="center" valign="middle" >0.83</td></tr><tr><td align="center" valign="middle" >Food Producers</td><td align="center" valign="middle" >2.36</td><td align="center" valign="middle" >10.10</td><td align="center" valign="middle" >31.81</td><td align="center" valign="middle" >2.87</td><td align="center" valign="middle" >5.52</td></tr><tr><td align="center" valign="middle" >Forestry and Paper</td><td align="center" valign="middle" >1.43</td><td align="center" valign="middle" >6.97</td><td align="center" valign="middle" >51.40</td><td align="center" valign="middle" >12.61</td><td align="center" valign="middle" >2.07</td></tr><tr><td align="center" valign="middle" >Industrial Engineering</td><td align="center" valign="middle" >2.26</td><td align="center" valign="middle" >4.27</td><td align="center" valign="middle" >20.30</td><td align="center" valign="middle" >3.83</td><td align="center" valign="middle" >5.56</td></tr><tr><td align="center" valign="middle" >Industrial Metals and Mining</td><td align="center" valign="middle" >5.01</td><td align="center" valign="middle" >21.04</td><td align="center" valign="middle" >34.24</td><td align="center" valign="middle" >−3.52</td><td align="center" valign="middle" >12.35</td></tr><tr><td align="center" valign="middle" >Pharmaceuticals and Biotechnology</td><td align="center" valign="middle" >5.30</td><td align="center" valign="middle" >39.13</td><td align="center" valign="middle" >12.79</td><td align="center" valign="middle" >15.00</td><td align="center" valign="middle" >8.31</td></tr><tr><td align="center" valign="middle" >Technology Hardware and Equipment</td><td align="center" valign="middle" >1.92</td><td align="center" valign="middle" >7.59</td><td align="center" valign="middle" >12.90</td><td align="center" valign="middle" >27.11</td><td align="center" valign="middle" >7.43</td></tr></tbody></table></table-wrap></table-wrap-group><p>2) The highest capitalization in Fixed Assets is in Forestry and paper, Industrial metals, Food and Beverages and Metals,</p><p>3) The highest gross profit margin was realized in the sectors of Technology Equipment, Pharmaceuticals, Beverages and Forestry-Paper,</p><p>4) Investment in new equipment and machinery, a proxy for new technology application was noticed in the sectors of Ind. Metals, Pharmaceuticals and Technology Equipment, the ones with high capitalization.</p></sec></sec><sec id="s4"><title>4. Results and Discussions</title><p>In <xref ref-type="table" rid="table5">Table 5</xref> and <xref ref-type="table" rid="table6">Table 6</xref>, the performance characteristics of manufacturing firms per region are presented. The results can issue significant indicators about the differences between the financial characteristics of manufacturing firms of Balkan, European and Scandinavian countries.</p><p>Scandinavian firms are the largest and present the highest profitability among others. European firms exhibited the highest Total Assets growth and have the highest inventory efficiency, while Balkan countries have the mostly heavily levered firms. Scandinavian firms are the ones with the highest labor productivity [<xref ref-type="bibr" rid="scirp.69993-ref25">25</xref>] .</p><p>European and Scandinavian countries show adequate interest coverage ratios and liquidity. Scandinavian firms show no to be affected by the economic crisis with 22.2% average annual sales growth rate. European firms follow with a 10% rate while Balkan firms seem to be hit by the crisis with a negative growth rate of −1.15%. Gross profit margin growth rate is around 10% for both European and Scandinavian countries and only 1.35% for the Balkan manufacture. Scandinavian firms showed the highest investments in Net Fixed Assets.</p><table-wrap-group id="5"><label><xref ref-type="table" rid="table5">Table 5</xref></label><caption><title> Descriptive statistics per region (average)</title></caption><table-wrap id="5_1"><caption><title> (b)</title></caption><table><tbody><thead><tr><th align="center" valign="middle" >Regions</th><th align="center" valign="middle" >Return on Assets (ROA)</th><th align="center" valign="middle" >Total Assets (Average)</th><th align="center" valign="middle" >Total Assets Growth</th><th align="center" valign="middle" >Total Debt/Equity (%)</th><th align="center" valign="middle" >Change in Machinery &amp; Equipment (%)</th><th align="center" valign="middle" >Inventory turnover</th><th align="center" valign="middle" >Sales per Employee</th></tr></thead><tr><td align="center" valign="middle" >BALKANS (BALK)</td><td align="center" valign="middle" >−37.80%</td><td align="center" valign="middle" >320,121.61</td><td align="center" valign="middle" >−3.07%</td><td align="center" valign="middle" >152.69</td><td align="center" valign="middle" >−1.58</td><td align="center" valign="middle" >28.92342</td><td align="center" valign="middle" >288.77</td></tr><tr><td align="center" valign="middle" >EUROPEAN (EUR)</td><td align="center" valign="middle" >10.62%</td><td align="center" valign="middle" >4,627,769.52</td><td align="center" valign="middle" >22.70%</td><td align="center" valign="middle" >104.37</td><td align="center" valign="middle" >−7.35</td><td align="center" valign="middle" >39.07034</td><td align="center" valign="middle" >435.35</td></tr><tr><td align="center" valign="middle" >SCANDINAVIAN (SCAND)</td><td align="center" valign="middle" >30.12%</td><td align="center" valign="middle" >15,342,688.1</td><td align="center" valign="middle" >13.84%</td><td align="center" valign="middle" >86.96</td><td align="center" valign="middle" >−6.09</td><td align="center" valign="middle" >17.05426</td><td align="center" valign="middle" >1562.27</td></tr><tr><td align="center" valign="middle" >t-test</td><td align="center" valign="middle" >1.9612</td><td align="center" valign="middle" >2.9856</td><td align="center" valign="middle" >−7.1854</td><td align="center" valign="middle" >19.7918<sup>*</sup></td><td align="center" valign="middle"  rowspan="2"  >−1.0275 (0.0679)</td><td align="center" valign="middle" >0.5987</td><td align="center" valign="middle" >1.6985<sup>**</sup></td></tr><tr><td align="center" valign="middle" >(BALK-EUR)</td><td align="center" valign="middle" >(0.0067)<sup>*</sup></td><td align="center" valign="middle" >(0.0007)<sup>*</sup></td><td align="center" valign="middle" >(0.0000)<sup>*</sup></td><td align="center" valign="middle" >(0.0000)</td><td align="center" valign="middle" >(1.0615)</td><td align="center" valign="middle" >(0.0486)</td></tr><tr><td align="center" valign="middle" >t-test</td><td align="center" valign="middle" >1.9617</td><td align="center" valign="middle" >2.527</td><td align="center" valign="middle" >4.5638</td><td align="center" valign="middle" >1.9275<sup>**</sup></td><td align="center" valign="middle"  rowspan="2"  >−1.0074 (0.0771)</td><td align="center" valign="middle" >0.3708</td><td align="center" valign="middle" >15.9476<sup>*</sup></td></tr><tr><td align="center" valign="middle" >(BALK-SCAND)</td><td align="center" valign="middle" >(0.0261)<sup>**</sup></td><td align="center" valign="middle" >(0.00000)<sup>*</sup></td><td align="center" valign="middle" >(0.0005)<sup>*</sup></td><td align="center" valign="middle" >(0.0339)</td><td align="center" valign="middle" >(0.7107)</td><td align="center" valign="middle" >(0.0000)</td></tr></tbody></table></table-wrap><table-wrap id="5_2"><caption><title></title></caption><table><tbody><thead><tr><th align="center" valign="middle" >REGIONS</th><th align="center" valign="middle" >Operating Expenses in Euros</th><th align="center" valign="middle" >Earnings Before Interest and Taxes (EBIT)/Total Interest Expenses</th><th align="center" valign="middle" >Quick Ratio</th><th align="center" valign="middle" >Sales Growth</th><th align="center" valign="middle" >Gross Profit Margin-Growth</th><th align="center" valign="middle" >Property, Plant, Equipment (PPE) Growth</th></tr></thead><tr><td align="center" valign="middle" >BALKANS (BALK)</td><td align="center" valign="middle" >296,809</td><td align="center" valign="middle" >0.936</td><td align="center" valign="middle" >0.9859</td><td align="center" valign="middle" >−1.15%</td><td align="center" valign="middle" >1.35%</td><td align="center" valign="middle" >−1.08%</td></tr><tr><td align="center" valign="middle" >EUROPEAN (EUR)</td><td align="center" valign="middle" >3,590,093</td><td align="center" valign="middle" >3.559</td><td align="center" valign="middle" >2.8505</td><td align="center" valign="middle" >10.83%</td><td align="center" valign="middle" >9.95%</td><td align="center" valign="middle" >5.19%</td></tr><tr><td align="center" valign="middle" >SCANDIVIAN (SCAND)</td><td align="center" valign="middle" >14,006,537</td><td align="center" valign="middle" >4.002</td><td align="center" valign="middle" >1.8676</td><td align="center" valign="middle" >22.21%</td><td align="center" valign="middle" >8.11%</td><td align="center" valign="middle" >10.32%</td></tr><tr><td align="center" valign="middle" >t-test</td><td align="center" valign="middle" >3.988<sup>*</sup></td><td align="center" valign="middle" >4.9282<sup>*</sup></td><td align="center" valign="middle" >2.818<sup>*</sup></td><td align="center" valign="middle" >−4.655<sup>*</sup></td><td align="center" valign="middle"  rowspan="2"  >5.415<sup>*</sup> (0.0000)</td><td align="center" valign="middle"  rowspan="2"  >−2.336<sup>*</sup> (0.002)</td></tr><tr><td align="center" valign="middle" >(BALK-EUR)</td><td align="center" valign="middle" >(0.0000)</td><td align="center" valign="middle" >(0.0000)</td><td align="center" valign="middle" >(0.0000)</td><td align="center" valign="middle" >(0.0000)</td></tr><tr><td align="center" valign="middle" >t-test</td><td align="center" valign="middle" >24.9276<sup>*</sup></td><td align="center" valign="middle"  rowspan="2"  >5.5236<sup>*</sup> (0.0000)</td><td align="center" valign="middle" >2.1927<sup>**</sup></td><td align="center" valign="middle" >8.2212<sup>*</sup></td><td align="center" valign="middle"  rowspan="2"  >5.1212<sup>*</sup> (0.0000)</td><td align="center" valign="middle"  rowspan="2"  >3.3356<sup>*</sup> (0.0000)</td></tr><tr><td align="center" valign="middle" >(BALK-SCAND)</td><td align="center" valign="middle" >(0.0000)</td><td align="center" valign="middle" >(0.0211)</td><td align="center" valign="middle" >(0.0000)</td></tr></tbody></table></table-wrap></table-wrap-group><p>Pairwise t-test, p values in parenthesis. (<sup>*</sup>), (<sup>**</sup>) significance at 1%, 5% respectively.</p><p>Pairwise t-test, p values in parenthesis. (<sup>*</sup>), (<sup>**</sup>) significance at 1%, 5% respectively.</p><table-wrap id="table6" ><label><xref ref-type="table" rid="table6">Table 6</xref></label><caption><title> Tobit regression results</title></caption><table><tbody><thead><tr><th align="center" valign="middle" >Region</th><th align="center" valign="middle" >Constant</th><th align="center" valign="middle" >Export Value Index</th><th align="center" valign="middle" >R&amp;D expenditure (% of GDP)</th><th align="center" valign="middle" >FDI, Net Inflows (% of GDP)</th></tr></thead><tr><td align="center" valign="middle"  rowspan="2"  >Austria</td><td align="center" valign="middle" >0.5058</td><td align="center" valign="middle" >0.27</td><td align="center" valign="middle" >47.28</td><td align="center" valign="middle" >0.17</td></tr><tr><td align="center" valign="middle" >(0.013)<sup>**</sup></td><td align="center" valign="middle" >(0.0329)<sup>**</sup></td><td align="center" valign="middle" >(0.0000)<sup>*</sup></td><td align="center" valign="middle" >(0.0086)<sup>*</sup></td></tr><tr><td align="center" valign="middle"  rowspan="2"  >Belgium</td><td align="center" valign="middle" >42.04</td><td align="center" valign="middle" >0.72</td><td align="center" valign="middle" >0.45</td><td align="center" valign="middle" >3.55</td></tr><tr><td align="center" valign="middle" >(0.020)<sup>**</sup></td><td align="center" valign="middle" >(0.0130)<sup>**</sup></td><td align="center" valign="middle" >(0.008)<sup>*</sup></td><td align="center" valign="middle" >(0.007)<sup>*</sup></td></tr><tr><td align="center" valign="middle"  rowspan="2"  >Bulgaria</td><td align="center" valign="middle" >21.63</td><td align="center" valign="middle" >5.71</td><td align="center" valign="middle" >0.25</td><td align="center" valign="middle" >3.85</td></tr><tr><td align="center" valign="middle" >(0.0800)</td><td align="center" valign="middle" >(0.046)<sup>**</sup></td><td align="center" valign="middle" >(0.085)</td><td align="center" valign="middle" >(0.032)<sup>**</sup></td></tr><tr><td align="center" valign="middle"  rowspan="2"  >Denmark</td><td align="center" valign="middle" >74.82</td><td align="center" valign="middle" >8.03</td><td align="center" valign="middle" >10.55</td><td align="center" valign="middle" >3.67</td></tr><tr><td align="center" valign="middle" >(0.017)<sup>**</sup></td><td align="center" valign="middle" >(0.19)</td><td align="center" valign="middle" >(0.0052)<sup>*</sup></td><td align="center" valign="middle" >(0.045)<sup>**</sup></td></tr><tr><td align="center" valign="middle"  rowspan="2"  >Finland</td><td align="center" valign="middle" >80.67</td><td align="center" valign="middle" >3.33</td><td align="center" valign="middle" >4.20</td><td align="center" valign="middle" >8.26</td></tr><tr><td align="center" valign="middle" >(0.0004)<sup>*</sup></td><td align="center" valign="middle" >(0.080)</td><td align="center" valign="middle" >(0.038)<sup>**</sup></td><td align="center" valign="middle" >(0.0075)<sup>*</sup></td></tr><tr><td align="center" valign="middle"  rowspan="2"  >France</td><td align="center" valign="middle" >15.9</td><td align="center" valign="middle" >0.66</td><td align="center" valign="middle" >8.11</td><td align="center" valign="middle" >3.59</td></tr><tr><td align="center" valign="middle" >(0.0000)<sup>*</sup></td><td align="center" valign="middle" >(0.067)</td><td align="center" valign="middle" >(0.0003)<sup>*</sup></td><td align="center" valign="middle" >(0.0001)<sup>*</sup></td></tr><tr><td align="center" valign="middle"  rowspan="2"  >Germany</td><td align="center" valign="middle" >23.04</td><td align="center" valign="middle" >0.546</td><td align="center" valign="middle" >10.23</td><td align="center" valign="middle" >10.72</td></tr><tr><td align="center" valign="middle" >(0.0034)<sup>*</sup></td><td align="center" valign="middle" >(0.0064)<sup>*</sup></td><td align="center" valign="middle" >(0.0000)<sup>*</sup></td><td align="center" valign="middle" >(0.000)<sup>*</sup></td></tr><tr><td align="center" valign="middle"  rowspan="2"  >Greece</td><td align="center" valign="middle" >10.65</td><td align="center" valign="middle" >0.95</td><td align="center" valign="middle" >0.22</td><td align="center" valign="middle" >8.01</td></tr><tr><td align="center" valign="middle" >(0.0000)<sup>*</sup></td><td align="center" valign="middle" >(0.58)</td><td align="center" valign="middle" >(0.18)</td><td align="center" valign="middle" >(0.0056)<sup>*</sup></td></tr><tr><td align="center" valign="middle"  rowspan="2"  >Italy</td><td align="center" valign="middle" >78.1</td><td align="center" valign="middle" >2.26</td><td align="center" valign="middle" >0.025</td><td align="center" valign="middle" >10.85</td></tr><tr><td align="center" valign="middle" >(0.0040)<sup>*</sup></td><td align="center" valign="middle" >(0.0039)<sup>*</sup></td><td align="center" valign="middle" >(0.0001)<sup>*</sup></td><td align="center" valign="middle" >(0.0036)<sup>*</sup></td></tr><tr><td align="center" valign="middle"  rowspan="2"  >Lithuania</td><td align="center" valign="middle" >18.24</td><td align="center" valign="middle" >2.06</td><td align="center" valign="middle" >0.04</td><td align="center" valign="middle" >21.12</td></tr><tr><td align="center" valign="middle" >(0.0000)<sup>*</sup></td><td align="center" valign="middle" >(0.70)</td><td align="center" valign="middle" >(0.003)<sup>*</sup></td><td align="center" valign="middle" >(0.0000)<sup>**</sup></td></tr><tr><td align="center" valign="middle"  rowspan="2"  >Norway</td><td align="center" valign="middle" >98.23</td><td align="center" valign="middle" >1.06</td><td align="center" valign="middle" >10.05</td><td align="center" valign="middle" >5.12</td></tr><tr><td align="center" valign="middle" >(0.0000)<sup>*</sup></td><td align="center" valign="middle" >(0.060)</td><td align="center" valign="middle" >(0.002)<sup>*</sup></td><td align="center" valign="middle" >(0.0042)<sup>*</sup></td></tr><tr><td align="center" valign="middle"  rowspan="2"  >Portugal</td><td align="center" valign="middle" >8.23</td><td align="center" valign="middle" >1.89</td><td align="center" valign="middle" >0.24</td><td align="center" valign="middle" >1.12</td></tr><tr><td align="center" valign="middle" >(0.0000)<sup>*</sup></td><td align="center" valign="middle" >(0.53)</td><td align="center" valign="middle" >(0.02)<sup>*</sup></td><td align="center" valign="middle" >(0.42)</td></tr><tr><td align="center" valign="middle"  rowspan="2"  >Spain</td><td align="center" valign="middle" >98.23</td><td align="center" valign="middle" >1.06</td><td align="center" valign="middle" >7.05</td><td align="center" valign="middle" >10.25</td></tr><tr><td align="center" valign="middle" >(0.00)<sup>*</sup></td><td align="center" valign="middle" >(0.53)</td><td align="center" valign="middle" >(0.002)<sup>*</sup></td><td align="center" valign="middle" >(0.052)<sup>**</sup></td></tr><tr><td align="center" valign="middle"  rowspan="2"  >Sweden</td><td align="center" valign="middle" >58.38</td><td align="center" valign="middle" >110.8</td><td align="center" valign="middle" >11.2</td><td align="center" valign="middle" >80.63</td></tr><tr><td align="center" valign="middle" >(0.0000)<sup>*</sup></td><td align="center" valign="middle" >(0.0048)<sup>*</sup></td><td align="center" valign="middle" >(0.0015)<sup>*</sup></td><td align="center" valign="middle" >(0.0000)<sup>*</sup></td></tr><tr><td align="center" valign="middle"  rowspan="2"  >United Kingdom</td><td align="center" valign="middle" >25.6</td><td align="center" valign="middle" >40.03</td><td align="center" valign="middle" >40.73</td><td align="center" valign="middle" >10.79</td></tr><tr><td align="center" valign="middle" >(0.0000)<sup>*</sup></td><td align="center" valign="middle" >(0.0008)<sup>*</sup></td><td align="center" valign="middle" >(0.0000)<sup>*</sup></td><td align="center" valign="middle" >(0.021)<sup>*</sup></td></tr></tbody></table></table-wrap><p>Notes: <sup>*</sup>, <sup>**</sup>statistical significance at 1%, 5% level respectively (prob. of t-stats in parenthesis). Dependent variable: sales per number of employee, a proxy for competitiveness.</p><p>There are many definitions of competitiveness but no agreement on it. The definition may range from the ability to compete, to the capacity of ensuring high profitability, or the aptitude to gain market shares. If a firm is operationally efficient, cost effective and quality conscious, it can provide customers with more value and satisfaction and thus be competitive [<xref ref-type="bibr" rid="scirp.69993-ref26">26</xref>] [<xref ref-type="bibr" rid="scirp.69993-ref27">27</xref>] .</p><p>According to Reference [<xref ref-type="bibr" rid="scirp.69993-ref28">28</xref>] , resource based approach, the most commonly used indicators of competitiveness of a firm are operating performance, market performance and profitability. According to Reference [<xref ref-type="bibr" rid="scirp.69993-ref29">29</xref>] , competitiveness in the manufacturing sector is the ability to gain sustainable profits and maintain market share. In most studies, profitability, efficiency or productivity are used as proxies for competitiveness. In the present study, we use the ratio of sales over number of employees, a measure of productivity, as a proxy for competitiveness [<xref ref-type="bibr" rid="scirp.69993-ref30">30</xref>] .</p><p>The findings suggest that for all countries except of Greece and Bulgaria, R&amp;D came as a significant determinant of firm level competitiveness. It is especially important for Austria and UK (Due to the lack of data we didn’t insert Montenegro’s firms in the econometric model, for consistency reasons). FDI is a significant determinant too for all countries at 1% and 5% level of significance, but more critical for Sweden and Lithuania, as indicated by their high coefficient. Export activity is an indication of firm competitiveness but only for Austria, Belgium, Bulgaria, Germany, Italy, Sweden and UK.</p></sec><sec id="s5"><title>5. Concluding Observations/Policy Implications</title><p>The present empirical research suggests that the Scandinavian manufacturing firms are the most dynamic in terms of growth, have the best financial performance and do not show to have been hit by the economic crisis. European firms are in between with Balkan firms showing the worst performance as expected. After 2010, European and Scandinavian firms show an improvement in their profitability, while Balkan countries present significant reduction.</p><p>The largest manufacturing firms are in the Scandinavian countries and the smallest in the Balkans with European firms falling in between. European firms are the most effective in the management of their inventories as a strategy to overcome financing problems, thus achieving a high liquidity. Labor productivity is the highest in the Scandinavian countries. This can be explained by the size of the firms and the capital intensity and use of new technology (highest net fixed asset growth). R&amp;D, FDI and export intensity were found to affect positively and significantly the competitiveness of manufacturing firms in the examined countries, measured in terms of labor productivity. Availability of low cost financing, R&amp;D, innovation, FDI and labor productivity should be supported by policy makers.</p><p>The development of technological and R&amp;D cooperation among European, Scandinavian and Balkan manufacturing firms is also suggested for a convergence of financial performance and growth of their manufacture. In addition, a separation of the North and South European countries and Greece with a comparative analysis of their firms’ performance can be also included.</p></sec><sec id="s6"><title>Cite this paper</title><p>Christos Lemonakis,Konstantinos Vassakis,Alexandros Garefalakis,Xanthi Partalidou, (2016) Manufacturing Firms’ Performance and Productivity: Evidence from North and South European, Scandinavian and Balkan Countries. Theoretical Economics Letters,06,789-797. doi: 10.4236/tel.2016.64083</p></sec></body><back><ref-list><title>References</title><ref id="scirp.69993-ref1"><label>1</label><mixed-citation publication-type="other" xlink:type="simple">Dambolena, I.G. and Khoury, S.J. (1980) Ratio Stability and Corporate Failure. Journal of Finance, 35, 1017-1026.  
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