The relative performance of small cap firms and default risk across the business cycle: international evidence.
The time-varying nature of the firm size effect has been the subject of growing interest, particularly in the aftermath of the recent financial crisis. Small-cap firms provide a significant nexus for entrepreneurship and innovation and hence might be viewed as less prone to governance problems than large firms. (1) This could in part explain the superior performance of small-cap firms over long time horizons, and during times of recovery from economic downturns. Lower productivity and high exposure to debt may in part explain their underperformance over recessions, as reported in the academic literature (2) and in the popular press. (3)
Kim and Burnie (2002) suggest that the time-varying nature of the firm size effect may be attributable to the business cycle per se, as captured by dummy variables in their regression model. Smaller firms may also suffer from relatively lower productivity and high financial leverage during downturns (Chan and Chen, 1991). More recently, Switzer (2010) shows that the US small cap premium is significantly related to default risk in the economy, which may impact investments in R&D and innovation. This paper extends previous work that has focused on the US to look at the impact of the business cycle on the small cap premium internationally, in particular, for stocks in G-7 countries and in the Middle-East North African (MENA) region. New evidence is presented indicating that default risk, which may be tied to innovative investments, is not priced in non-common law settings where protection of shareholders and creditors in bankruptcy states is limited.
The remainder of this paper is organized as follows. The data are described in Section II. Section III looks at the innovative efforts and performance of small-caps vs. large caps across countries over recent business cycle peaks and troughs. Section IV revisits the small cap premium for G-7 and MENA countries. As is shown therein, the small firm anomaly appears to be largely a North American phenomenon in the post 2000 period. Section V looks at business cycle effects and the impact of various risk factors on the time variation of the small firm premia across countries. The paper concludes with a summary in Section VI.
II. DESCRIPTION OF THE DATA
The small cap and large cap portfolios for the returns for France, Germany, Italy, Japan and the UK, are the Morgan Stanley portfolio size based series that begin in January 1995. The US small cap series is based on monthly returns on the Ibbotson/DFA small stock portfolio, which is available from January 1926. The U.S. large cap portfolio from Morningstar/Ibbotson is the S&P 500. The U.S. market portfolio proxy is the CRSP value weighted portfolio of NYSE, AMEX and NASDAQ stocks, which is available since 1926. The US risk free rate is the 1 month T-bill rate, from WRDS. For the series, the only continuous extant proxy for Canadian small firms is Nesbitt Burns Small Cap Index, which is available since producing a benchmark series in January 1987. The US risk factors are obtained from Morningstar EnCorr. Default risk (bond default premium) is measured by the geometric difference between total returns on long-term corporate bonds and long-term government bonds. Term Structure risk (bond horizon premium) is measured by the geometric difference between Government Long Bond and Treasury Bill Returns. Inflation is based on the US consumer price index. R&D and sales data of firms are from COMPUSTAT, with the S&P 600 Small Cap index used as the reference for compiling the small-cap company data. The business cycle peaks and troughs are based on the National Bureau of Economic Research (NBER) dates.
III. DIFFERENTIAL RETURNS AND INNOVATIVE EFFORTS FOR SMALL-CAPS AND LARGE CAPS ACROSS COUNTRIES
Figure 1 illustrates the differential returns for small-caps vs. large-caps for the G-7 countries. Recession intervals are highlighted with the grey shading of the graphs. Except for Germany, small caps outperformed for the sample holding period from January 1995-December 2011.
[FIGURE 1 OMITTED]
Table 1 provides some descriptive statistics for the small-cap premia across G-7 countries. Again, with the exception of Germany, the average premia are positive over the sample period. We cannot reject the hypothesis of equality of means for these premia across countries.
Table 2 below shows the R&D intensity and stock market performance of US firms by market capitalization over the past decade. Large cap stocks are presented in Panel A, while small-caps are shown in Panel B. On average, the R&D to sales ratio of small caps is roughly doubles that of large caps. Furthermore, while there is considerable variation from year to year, the average performance of small caps is quite impressive. Note that both small caps and large did poorly during 2008, a recessionary year, while small caps performed relatively worse at the onset of the recession in 2007. Both groups appear to have reduced their R&D intensity since 2008, however.
Table 3 shows the G7, European Union, Asian, and MENA Small Cap Premia as well as the country aggregated R&D Expenditure as a Percentage of GDP for two most recent recessionary intervals, March 2001-November 2001 and December 2007-June 2009. It is evident that small caps do not perform well over recessionary periods. Japan, which is the country with the highest R&D intensity, is an exception to this trend.
On the whole, recoveries are beneficial for markets in general. They are especially propitious for small-caps.
IV. THE SMALL STOCK PREMIUM ANOMALY REVISITED
One of the oldest challenges to the efficient markets paradigm is the small firm (small-cap) anomaly (e.g., Banz, 1981; Reinganum, 1981a, 1981b; Siegel, 1998; Hawawini and Keim, 1999). Dimson and Marsh (1999) state that the striking outperformance of small cap companies is "the premier stock market anomaly" that is inconsistent with market efficiency. On the other hand, Bhardwaj and Brooks (1993), Horowitz et al (2000) and Schwert (2003) challenge the small-firm anomaly, Based on returns that extend to the 1982-2002 period, the latter concludes (2003, p. 943) the "small-firm anomaly has disappeared since the initial publication of the papers that discovered it." The issue of small stock outperformance remains a topic of debate across countries. Switzer and Fan (2007) show that the high returns to small caps may be country dependent, and demonstrate the benefits of adding Canadian small caps for international investors in enhancing their risk-return performance. More recently, Switzer (2010) shows that the small cap anomaly has re-appeared for most recent decade for US stocks.
Table 5 provides estimates of the Jensen (1968) alpha performance regression using the excess returns of the various small cap portfolios of this study ([RS.sub.t]) over the risk free rate, proxied by the one month T-bill rate ([RF.sub.t]) as the dependent variable; the independent variables consist of a constant and the excess of the CRSP value weighted portfolio of NYSE, AMEX and NASDAQ stocks benchmark market index ([RM.sub.t]) over the one month treasury bill as the risk free rate ([RF.sub.t]); e is the random error term.
[RS.sub.t] - [RF.sub.t] = [alpha] + [beta]([RM.sub.t] - [RF.sub.t]) + [[epsilon].sub.t]
The intercept of the regression measures the Jensen (1968) [alpha], shows the difference between the monthly return of the small cap portfolio and the Capital Asset Pricing Model. It is evident that the small stock premium is only a North American phenomenon. In the post 2000 period it is not significant (at the 5% level) for the other G-7 countries of this study or for the MENA region. (8)
V. BUSINESS CYCLE TURNING POINTS AND OTHERS RISK DETERMINANTS OF THE SMALL CAP PREMIUM
How does the small-cap premium behave over the business cycle for the countries of this study? Kim and Burnie (2002) assert that the small firm effect is only observed during business cycle expansions, and not contractions. However, they do not directly account for differential risk exposures that firms may face that have been postulated to be significant factors affecting the returns to firms (Chen, Roll, and Ross, 1986; Ferson and Harvey, 1991) and that may work apart from the state of the business cycle per se in affecting the return differential between large cap and small cap firms. Switzer (2010) looks at three such risk exposures: default risk (DEF), term structure risk (TERM), and inflation risk (INFLATION). (10) He shows that the small cap premium is significantly related to default risk in the economy, consistent with Vasilou and Xing (2004). While the term structure and inflation coefficients are positive, however, they are not significant, indicating that interest rate risk and inflation risk do not differentially affect small cap vs. large cap firms. Furthermore, in contrast with Kim and Burney (2002), recessions per se do not affect the US small firm return premium.
We extend this analysis herein for our international sample. Table 6 reports the results of regression tests for the period 1995:01-2011:12 of the model:
[SML.sub.t] = [[alpha].sub.0] + [[alpha].sub.1][DEF.sub.t] + [[alpha].sub.2][TERM.sub.t] + [[alpha].sub.3] [INFLATION.sub.t] + [2.summation over (i=1)][[delta].sub.i][RECESSION.sub.it] + [[epsilon].sub.t] (1)
where SML is the small cap premium, DEF is default risk (bond default premium), TERM is term structure (bond horizon risk), INFLATION is the monthly inflation rate (consumer price index), [DUM.sub.i] is a dummy variable for the recession episode i, i = 1,2, [RECESSION.sub.i] is a dummy variable for the recession episode i, i = 1, 2; [RECESSION.sub.1]--2001 Recession; [RECESSION.sub.2]--2007-09 Recession; [[epsilon].sub.i] is a random error term.
Overall, the results are quite different, by country and region. Inflation risk is priced in both France and Italy. Mild term structure risk is found in Germany and Japan. Default risk is significant in North American markets and the UK. Default risk, which may be tied to innovative investments, is not priced in non-common law settings, where protection of shareholders and creditors in bankruptcy states is limited. This result is consistent with La Porta et al. (1998). The recession dummy variables are not significant for any of the countries These factors are distinct from business cycle turning points per se, which are not found to be significant. It should be noted that these conclusions also hold when we use the OECD recession dates for each country, as well as country specific measures of default risk, term-structure risk, and inflation risk. The detailed results using these alternative variables are available on request.
This paper provides a new look at the small cap premium in international markets. Since 2000, economically and statistically significant abnormal returns are observed for small cap stocks in North America, but not in other G-7 countries or in the MENA region. Size based asset portfolios are found to be associated with risk factors that differ across countries. These factors are distinct from business cycle turning points per se, which are not found to be significant.
A more in-depth analysis of the links between default risk, innovation, and performance across asset classes remains a topic for future research. The factors that drive innovation and differential performance across asset size classes should be of considerable interest for investors looking to benefit from time-varying asset allocation strategies (see, e.g., Arshanapalli, Switzer, and Panju (2007)).
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(1.) According to the U.S. Small Business Administration, small firms:
* "Represent 99.7 percent of all employer firms.
* Employ about half of all private sector employees.
* Pay nearly 45 percent of total U.S. private payroll.
* Have generated 60 to 80 percent of net new jobs annually over the last decade.
* Create more than half of nonfarm private gross domestic product (GDP).
* Hire 40 percent of high tech workers (such as scientists, engineers, and computer workers).
* Made up 97.3 percent of all identified exporters and produced 28.9 percent of the known export value in FY 2006.
* Produce 13 times more patents per employee than large patenting firms; these patents are twice as likely as large firm patents to be among the one percent most cited." See http://web.sba.gov/faqs/faqindex.cfm?areaID=24
(2.) See, e.g., Schwert (1990) and Fama and French (1995), and Switzer and Tang (2009). Moscarini and Postel-Vinay (2009) suggest that the small cap premium is linked to job creation: large employers destroy proportionally more jobs during and immediately after recessions occur, and create proportionally more jobs late in expansions, relative to small employers. This differential is also shown to explain in part the superior performance of US small cap firms during recoveries (Moscarini and Postel-Vinay (2010)).
(3.) An analyst in the Financial Times (Handy Caps, May 26, 2009, p12 states: "The final stages of a boom, though, are an inauspicious time to own small companies. As the economy slows, they are often the first to feel the pinch: small businesses tend to be biased towards cyclical industries and mostly do not have the luxury of international diversification. Also, as bull markets near their apex, inflows from naive retail investors may be concentrated in the largest, most liquid shares. True to form, small caps began to underperform the broader US market just as the housing bubble peaked. From April 2006 to the end of 2008, they shed 32 per cent of their value compared with just 24 per cent for large stocks. Conversely, much of small stocks' historical edge comes from outperforming early in any recovery...."
(4.) UNESCO Institure for Statistics, Beyond 20/20 WDS, 2012, 27 January 2012 <http://stats.uis.unesco.org/unesco/TableViewer/tableView.aspx>.
(5.) http://epp.eurostat.ec.europa.eu/cache/ITY_PUBLIC/ 9-08092009-AP/EN/9-08092009-AP-EN.PDF
(6.) This estimate excludes Malaysia, Taiwan, and the Philippines due to the lack of available data.
(7.) This estimate excludes Malaysia, Taiwan, and Indonesia due to the lack of available data.
(8.) The Jensen alpha is only significant for MENA countries at the 10% level.
(9.) http://www.oecd-ilibrary.org/sites/rdxp-table-2011-en/ index.html;jsessionid=9u933p450d7f.delta?contentType=/ns/KeyTable,/ns/Stati sticalPublication&itemId=/content/table/2075843x- table1&containerItemId=/content/tablecollection/2075843x&accessItemIds=&mim eType=text/html
(10.) Default risk or the bond default premium, is measured by the long term corporate to government yield spreads (DEF). A positive default risk premium is consistent with investors' desire to hedge against unanticipated increases in the aggregate risk premium induced by an increase in uncertainty in the economy (Ferson and Harvey, 1991). In Fama and French (1995) the small firm premium is a proxy for a default risk state variable. Vasilou and Xing (2004) show that default risk does affect the Fama and French (1995) size and book to market factors. Beck and Demirguc-Kunt (2006) assert that small and medium size firms are more exposed to default risk due to their lack of capital and liquidity compared to large firms. A rising term reflects an increase in riskiness of longer term assets, To the extent that small cap firms bear a distinct risk premium, this priced to the extent that investors require a higher premium to hold risky assets when the term structure becomes steeper. Inflation risk has been attributed as a significant factor in adversely affecting stock returns, and in the asset allocation (e.g., Fama, 1981; Boudoukh and Richardson, 1993; Bekaert, 2009; Katzur and Spierdijk, 2010). To the extent that small firms operate in more competitive environments, they may have less pricing power than larger firms, and hence may be more exposed to inflation risk, and hence command an inflation premium relative to larger firms.
Lorne N. Switzer *
Van Berkom Endowed Chair of Small-Cap Equities and Associate Director, Institute for Governance in Private and Public Organizations, John Molson School of Business Concordia University, 1455 de Maisonneuve Blvd. W. Montreal, Quebec, Canada H3G 1M8
* I would like to the Editor, K.C. Chen, and J.M. Sahut for their helpful comments as well as Easton Sheehan-Lee and Yan Gao for their capable research assistance. Financial support from the SSHRC and the Autorite des Marches Financiers is gratefully acknowledged.
Table 1 U.S. R&D intensity vs. stock market returns, 2000-2010 This table shows the R&D to sales ratio and annualized total stock returns (returns including dividends) for U.S. large cap vs. small Cap firms. S&P 500 Firms represent the Large-Cap Sector. The Small Cap Companies are from the S&P 600 Small-Cap Index. The data are from COMPUSTAT. Panel A. Large Caps Year R&D/Sales Annualized Return 2000 0.090786014 -0.0910 2001 0.091573332 -0.1189 2002 0.092031455 -0.2210 2003 0.093892787 0.2869 2004 0.077204206 0.1088 2005 0.073206480 0.0491 2006 0.084039733 0.1579 2007 0.077582268 0.0549 2008 0.080155903 -0.3700 2009 0.075663921 0.2646 2010 0.071601502 0.1506 Mean 0.082521600 0.0247 Median 0.080155903 0.0549 StdDev 0.008267989 0.2046 Panel B. Small Caps Year R&D/Sales Annualized Return 2000 0.277975336 0.1180 2001 0.222472441 0.0654 2002 0.181341365 -0.1463 2003 0.240879096 0.3879 2004 0.093737142 0.2265 2005 0.103199740 0.0665 2006 0.116962567 0.1407 2007 0.124811868 -0.0122 2008 0.172236788 -0.3199 2009 0.169837676 0.2378 2010 0.119315386 0.2498 Mean 0.165706309 0.0922 Median 0.169837676 0.1180 StdDev 0.060884238 0.1984 Table 2 Descriptive statistics for monthly small cap premia, G-7 countries Jan. 1995-December 2011 Canada France Germany Italy Mean 0.000749 -0.000608 -0.001859 0.000320 Median 0.000326 1.71E-05 -0.002809 0.003666 Maximum 0.139315 0.091470 0.144177 0.074924 Minimum -0.110480 -0.088943 -0.119634 -0.097419 Std. Dev. 0.034121 0.033778 0.037187 0.033142 Skewness -0.153227 0.069265 0.134850 -0.520449 Kurtosis 5.203032 3.137464 3.646435 3.101895 Jarque-Bera 38.13516 0.293587 3.781836 8.431761 Probability 0.000000 0.863472 0.150933 0.014759 Sum 0.138562 -0.112486 -0.343871 0.059241 Sum Sq. Dev. 0.214224 0.209931 0.254442 0.202100 Japan UK US Mean 0.001137 0.001261 0.003461 Median 0.002015 0.001999 0.001178 Maximum 0.140879 0.094272 0.259645 Minimum -0.103263 -0.110141 -0.157520 Std. Dev. 0.032439 0.033961 0.044707 Skewness 0.107693 -0.194848 0.933342 Kurtosis 5.162743 3.811532 8.638182 Jarque-Bera 36.41301 6.247191 271.9007 Probability 0.000000 0.043999 0.000000 Sum 0.210398 0.233246 0.640357 Sum Sq. Dev. 0.193627 0.212211 0.367768 Test for Equality of Means Between the Premia Method df Value Probability Anova F-test (6, 1288) 0.396301 0.8817 Welch F-test * (6, 571.952) 0.320498 0.9263 * Test allows for unequal cell variances Table 3 G7 small cap premium and R&D expenditure as a percentage of GDP (4) for recessionary periods Country March 2001 December 2007 (Small Cap Premium/ R&D (Small Cap Premium/R&D as % of GDP for 2001) as % of GDP for 2007) France 4.65% 2.20% -15.61% 2.08% Germany -8.01% 2.46% -12.94% 2.53% Italy -3.57% 1.09% -8.59% 1.18% Japan 1.05% 3.12% 2.13% NA UK 0.62% 1.79% -26.15% 1.78% Canada 14.40% 2.09% -16.54% 1.91% US 23.57% 2.72% -2.05% 2.67% EU Small Cap 0.86% 1.86% (5) -15.60% 1.85% MSCI Asia 15.71% 1.01% (6) -8.77% 1.26% (7) Table 4 G7 small cap premium including R&D expenditure as a percentage of GDP for recovery period Country November 2001 June 2009 (Small Cap Premium/R&D (Small Cap Premium/R&D as % of GDP for 2001) as % of GDP for 2009) France 10.95% 2.20% 40.85% 2.23% Germany 8.83% 2.46% 37.13% 2.82% Italy 16.01% 1.09% 23.93% 1.27% Japan 3.15% 3.12% 2.56% NA UK 9.73% 1.79% 29.48% 1.87% Canada 18.36% 2.09% 26.34% 1.95% US 10.36% 2.72% 9.04% No Data EU Small 15.59% 1.86% -3.23% 1.92% (9) Cap Table 5 Jensen (1968) alpha performance regressions for 2001:01-2011:12 of the G-7 and. Small Company Portfolio ([RS.sub.t]) using the CRSP value weighted portfolio of NYSE, AMEX and NASDAQ stocks ([RM.sub.t]) as the benchmark market index, and the U.S. one month treasure bill as the risk free rate ([RF.sub.t]); e is the random error term. The intercept of the regression measures the Jensen (1968) alpha, shows the difference between the monthly return of the small cap portfolio and the Capital Asset Pricing Model: [RS.sub.t] - [RF.sub.t] = [alpha] + [beta]([RM.sub.t] - [RF.sub.t]) + [[epsilon].sub.t] Estimated Coefficient [alpha] [beta] France 0.0022 0.6089 *** 0.6685 t-statistic 0.6089 16.1390 Germany 0.0025 1.3251 *** 0.7184 t-statistic 0.7348 18.2120 Italy -0.0001 1.0841 *** 0.5747 t-statistic -0.2256 13.2550 Japan 0.0024 0.4204 *** 0.1558 t-statistic 0.5840 14.8981 UK 0.0033 1.0752 *** 0.6375 t-statistic 0.9662 15.1211 US 0.0053 ** 1.1863 *** 0.8055 t-statistics 2.1700 23.2026 Canada 0.0087 ** 1.1712 *** 0.5933 t-statistic 2.1362 13.7740 MENA 0.0085 0.9552 0.3759 t-statistic 1.6374 * 8.8500 ***, **, * indicate significance at .01 level, .05 level, and .10 level, respectively Table 6 Results of regression tests for the period 1995:01-2011:12 of Equation (1) Panel A.: Canada Variable Coefficient Std. Error t-Statistic Prob. C 0.003053 0.003161 0.965553 0.3356 RECESSION2001 0.002357 0.011554 0.203964 0.8386 RECESSION2007 -0.009811 0.008184 -1.198803 0.2322 DEFAULTRISK 0.359586 0.150910 2.382783 0.0182 TERMRISK -0.026729 0.093084 -0.287147 0.7743 INFLATION -0.577858 0.694736 -0.831767 0.4066 R-squared 0.056538 Mean dependent var. 0.000749 Adjusted 0.030184 S.D. dependent var. 0.034121 R-squared S.E. of 0.033602 Akaike info criterion -3.916547 regression Sum squared 0.202112 Schwarz criterion -3.812103 resid Log likelihood 368.2806 Hannan-Quinn criter. -3.874218 F-statistic 2.145344 Durbin-Watson stat. 1.729828 Prob 0.062146 (F-statistic) Panel B: France Variable Coefficient Std. Error t-Statistic Prob. C -0.003020 0.003172 -0.952126 0.3423 RECESSION2001 -0.002682 0.011591 -0.231397 0.8173 RECESSION2007 -0.004189 0.008210 -0.510216 0.6105 DEFAULTRISK 0.226103 0.151393 1.493490 0.1371 TERMRISK 0.074464 0.093381 0.797418 0.4263 INFLATION 1.346015 0.696957 1.931275 0.0550 R-squared 0.031083 Mean dependent var. -0.000608 Adjusted 0.004018 S.D. dependent var. 0.033778 R-squared S.E. of 0.033710 Akaike info criterion -3.910164 regression Sum squared 0.203406 Schwarz criterion -3.805720 resid Log likelihood 367.6902 Hannan-Quinn criter. -3.867836 F-statistic 1.148464 Durbin-Watson stat. 2.097857 Prob 0.336594 (F-statistic) Pane: C: Germany Variable Coefficient Std. Error t-Statistic Prob. C -0.005435 0.003491 -1.556658 0.1213 RECESSION2001 -0.008490 0.012760 -0.665344 0.5067 RECESSION2007 0.006221 0.009038 0.688302 0.4922 DEFAULTRISK 0.114128 0.166655 0.684815 0.4943 TERMRISK 0.194915 0.102795 1.896142 0.0596 INFLATION 1.195005 0.767218 1.557582 0.1211 R-squared 0.031273 Mean dependent var. -0.001859 Adjusted 0.004213 S.D. dependent var. 0.037187 R-squared S.E. of 0.037108 Akaike info criterion -3.718068 regression Sum squared 0.246485 Schwarz criterion -3.613624 resid Log likelihood 349.9213 Hannan-Quinn criter. -3.675739 F-statistic 1.155700 Durbin-Watson stat. 2.152796 Prob 0.332909 (F-statistic) Panel D: Italy Variable Coefficient Std. Error t-Statistic Prob. C -0.003911 0.003112 -1.256837 0.2105 RECESSION2001 -0.000107 0.011372 -0.009448 0.9925 RECESSION2007 0.007088 0.008055 0.879942 0.3801 DEFAULTRISK 0.052521 0.148529 0.353607 0.7240 TERMRISK 0.101049 0.091615 1.102972 0.2715 INFLATION 1.514953 0.683775 2.215572 0.0280 R-squared 0.031247 Mean dependent var. 0.000320 Adjusted 0.004186 S.D. dependent var. 0.033142 R-squared S.E. of 0.033072 Akaike info criterion -3.948352 regression Sum squared 0.195785 Schwarz criterion -3.843908 resid Log likelihood 371.2226 Hannan-Quinn criter. -3.906024 F-statistic 1.154708 Durbin-Watson stat. 1.938293 Prob 0.333413 (F-statistic) Panel E: Japan Variable Coefficient Std. Error t-Statistic Prob. C -0.003067 0.002994 -1.024383 0.3070 RECESSION2001 0.012900 0.010942 1.178991 0.2400 RECESSION2007 0.008576 0.007750 1.106541 0.2700 DEFAULTRISK -0.182347 0.142908 -1.275977 0.2036 TERMRISK 0.164464 0.088148 1.865771 0.0637 INFLATION 0.891930 0.657894 1.355735 0.1769 R-squared 0.063948 Mean dependent var. 0.001137 Adjusted 0.037801 S.D. dependent var. 0.032439 R-squared S.E. of 0.031820 Akaike info criterion -4.025522 regression Sum squared 0.181245 Schwarz criterion -3.921078 resid Log likelihood 378.3608 Hannan-Quinn criter. -3.983193 F-statistic 2.445741 Durbin-Watson stat. 2.007254 Prob 0.035797 (F-statistic) Panel F: UK Variable Coefficient Std. Error t-Statistic Prob. C -0.000532 0.003177 -0.167551 0.8671 RECESSION2001 -0.001964 0.011611 -0.169147 0.8659 RECESSION2007 0.000889 0.008224 0.108103 0.9140 DEFAULTRISK 0.318161 0.151653 2.097955 0.0373 TERMRISK 0.010076 0.093542 0.107711 0.9143 INFLATION 0.939981 0.698156 1.346378 0.1799 R-squared 0.038191 Mean dependent var. 0.001261 Adjusted 0.011325 S.D. dependent var. 0.033961 R-squared S.E. of 0.033768 Akaike info criterion -3.906726 regression Sum squared 0.204107 Schwarz criterion -3.802282 resid Log likelihood 367.3722 Hannan-Quinn criter. -3.864398 F-statistic 1.421543 Durbin-Watson stat. 1.839660 0 218547 Panel G: US Variable Coefficient Std. Error t-Statistic Prob. C 0.002143 0.004174 0.513421 0.6083 RECESSION2001 0.014742 0.015254 0.966419 0.3351 RECESSION2007 -9.65E-05 0.010804 -0.008933 0.9929 DEFAULTRISK 0.384470 0.199235 1.929733 0.0552 TERMRISK -0.061367 0.122891 -0.499363 0.6181 INFLATION 0.542567 0.917203 0.591545 0.5549 R-squared 0.042122 Mean dependent var. 0.003461 Adjusted 0.015365 S.D. dependent var. 0.044707 R-squared S.E. of 0.044362 Akaike info criterion -3.360952 regression Sum squared 0.352277 Schwarz criterion -3.256508 resid Log likelihood 316.8880 Hannan-Quinn criter. -3.318623 F-statistic 1.574266 Durbin-Watson stat. 1.904700 Prob 0.169536 (F-statistic) Panel H: MENA (Middle East and North African) Countries Variable Coefficient Std. Error t-Statistic Prob. C 0.003473 0.003090 1.123962 0.2625 RECESSION2001 -0.005490 0.011294 -0.486082 0.6275 RECESSION2007 -0.011010 0.008000 -1.376258 0.1705 DEFAULTRISK 0.135260 0.147517 0.916910 0.3604 TERMRISK -0.105112 0.090991 -1.155195 0.2496 INFLATION -0.148641 0.679115 -0.218875 0.8270 R-squared 0.032845 Mean dependent var. 0.001179 Adjusted 0.005829 S.D. dependent var. 0.032943 R-squared S.E. of 0.032847 Akaike info criterion -3.962031 regression Sum squared 0.193125 Schwarz criterion -3.857587 resid Log likelihood 372.4878 Hannan-Quinn criter. -3.919702 F-statistic 1.215765 Durbin-Watson stat. 1.896102 Prob 0.303535 (F-statistic)
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|Author:||Switzer, Lorne N.|
|Publication:||International Journal of Business|
|Date:||Sep 4, 2012|
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