Labor Market Developments and Economic Policies: An Overview

A salient feature of the French labor market in the last two decades has been the slow growth of employment relative to population. As shown in Table 2, the working-age population of France has increased by about 20 percent since 1970, while employment—especially in the private sector—has grown very little by comparison. Put differently, labor force participation fell while unemployment and nonemployment increased sharply.⁴ These developments took place against a backdrop of substantial economic growth. With employment essentially stagnant, the increase in real GDP can be accounted for almost entirely by higher labor productivity, which in turn reflects some combination of capital deepening and technological change (Chart 2).

Table 2.

Demographic and Labor Market Flows

(In millions of persons, unless otherwise noted)

¹Individuals aged 16 to 64.

²Unemployed persons in percent of labor force.

³Persons of working age not employed, in percent of working-age population.

⁴Labor force in percent of working-age population.

Table 2.

Demographic and Labor Market Flows

(In millions of persons, unless otherwise noted)

		1970	1990	Change
Population		50.8	56.7	5.9
Working-age population1		31.6	37.4	5.8
Labor force		21.4	24.8	3.4
Employment		20.9	22.6	1.7
	Public	3.7	5.1	1.5
	Private	17.2	17.5	0.3
Unemployment		0.5	2.2	1.7
Memorandum items
	Unemployment rate2	2.5	8.9	6.4
	Nonemployment rate3	33.9	39.6	5.7
	Labor force participation rate4	67.8	66.3	–1.5

¹Individuals aged 16 to 64.

²Unemployed persons in percent of labor force.

³Persons of working age not employed, in percent of working-age population.

⁴Labor force in percent of working-age population.

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Table 2.

Demographic and Labor Market Flows

(In millions of persons, unless otherwise noted)

		1970	1990	Change
Population		50.8	56.7	5.9
Working-age population1		31.6	37.4	5.8
Labor force		21.4	24.8	3.4
Employment		20.9	22.6	1.7
	Public	3.7	5.1	1.5
	Private	17.2	17.5	0.3
Unemployment		0.5	2.2	1.7
Memorandum items
	Unemployment rate2	2.5	8.9	6.4
	Nonemployment rate3	33.9	39.6	5.7
	Labor force participation rate4	67.8	66.3	–1.5

¹Individuals aged 16 to 64.

²Unemployed persons in percent of labor force.

³Persons of working age not employed, in percent of working-age population.

⁴Labor force in percent of working-age population.

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France: Labor Market Indicators and Economic Performance

Sources: Institut national de la statistique et des études économiques database; Organization for Economic Cooperation and Development, analytical database; and IMF staff calculations.1 Labor force in percent of working-age population.2 In percent of working-age population.3 Real GDP divided by employment.

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Wages also increased substantially over this period, although their growth rate at times diverged markedly from that of labor productivity (Chart 3). For example, from 1970 to 1983, the ratio of real producer wages to labor productivity (which is equivalent to the share of labor income in GDP) rose markedly. In contrast, during the second half of the 1980s, wages increased much more slowly than productivity. It is not a trivial task to explain these changes in the share of labor. However, they appear to have been strongly correlated with the real price of oil—perhaps because higher energy prices sharply depressed the rate of return on the existing capital stock or because workers succeeded, in the wage bargaining process, in being compensated for the increase in real fuel prices.

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France: Wage Developments

Sources: Institut national de la statistique et des études économiques database; Organization for Economic Cooperation and Development, analytical database; and IMF staff calculations.1 Gross income from dependent employment divided by GDP deflator.2 Income from dependent employment net of taxes, deflated by consumer price index.3 Equivalent to share of labor in GDP.4 In Francs per barrel, divided by GDP deflator.

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The period since 1970 has also been characterized by substantial changes in economic policy, many of which fit into a larger pattern of expanding government social programs (Chart 4). This has been reflected in a remarkable rise in the ratio of general government current expenditure and revenue in relation to GDP. Most of this increase is accounted for by higher social spending—on health care, pensions for regular and early retirement, unemployment compensation, and welfare—and has been financed largely by continuing increases in social security taxes levied on labor income. It is of course legitimate to ask whether higher social spending and higher social security taxes were principally a cause or an effect of higher unemployment—a question that is further discussed in the next section.

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France: Indicators of Public Sector Activity

Sources: Institut national de la statistique et des études économiques database; Organization for Economic Cooperation and Development, analytical database; French authorities; and IMF staff calculations.1 Ratio of social security taxes to gross income from dependent employment.2 Social security benefits per capita in percent of average net wage.3 Social security benefits per capita in percent of minimum wage.

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Another way of looking at the expansion of social expenditure is to calculate the ratio of social benefits per capita to the average wage net of social security contributions (Chart 4).⁵ It appears that, on average, a French resident (of any age) in 1993 received social support payments equivalent to almost 30 percent of the average net wage and to almost 90 percent of the minimum wage. This represents a massive increase compared with 1970, when these ratios were about half as high as they are now. A possible implication could be that unemployment, or nonwork, has become materially more tolerable than it was a generation ago and may even be an attractive alternative to certain low-paying jobs. The data support this interpretation.

An important example of the trend toward more remunerative government social programs, and one that is thought to affect the labor market directly, is the average replacement rate of the unemployment insurance system.⁶ This rate became substantially more generous from 1970 until about 1982 (Chart 5).⁷ A sharp turnaround took place under the government of socialist Prime Minister Laurent Fabius in 1983. However, even under the conservative governments that held office from 1986 to 1988 and after 1993, benefits were never scaled back to the levels that prevailed until the early 1970s.

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France: Indicators of Labor Market Policy

Sources: French authorities; and IMF staff calculations.1 Unemployment benefits per unemployed person in percent of average wages.2 Minimum wage in percent of average gross wage.

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The legal minimum wage has also risen substantially in real terms.⁸ However, it has remained in a narrow band relative to average gross producer wages, ranging from a high of 45 percent in 1970 to a low of 40½ percent in 1980 (Chart 5).

Single-Equation Models of Unemployment and Nonemployment

One way to investigate general economic influences on the unemployment and nonemployment rates is to seek statistically significant correlations between these rates and other economic variables.⁹ Such an exercise—based on an ad hoc specification search—is preliminary to the more systematic structural investigation to be described in the next section.¹⁰

The statistical determinants of the unemployment rate and of the non-employment rate are analyzed using a general autoregressive distributed lag (ARDL) model that includes a large number of explanatory variables, including real GDP, real interest rates, the employment rate, the real price of oil, social security benefits, the replacement ratio of the unemployment insurance system, and minimum wages.¹¹

The principal result is that, for both the unemployment rate and the nonemployment rate, the only policy variable that matters is the ratio of social security expenditure to gross income from dependent employment (the “social benefit ratio”), and this variable has an extremely strong and robust influence.¹² Granger causality tests suggest that the direction of causation runs both from social security expenditure to the dependent variable and the other way around. An equally strong result is obtained if the social expenditure ratio is adjusted for the effects of the business cycle.

A Structural Model of the Labor Market

Estimation Results

The issues that arise when estimating a model of the kind presented here are discussed at some length in Karanassou and Snower (1993) and Chapter 1 of this volume. Briefly, the main problems are those of dealing with non-stationary variables and of ensuring that the model, which is a simultaneous one, is estimated consistently. To allow for the presence of nonstationary variables, tests of cointegration among these nonstationary variables have been conducted.¹⁴ The estimated models are dynamic structural equations, and each equation is estimated as an “error correction” model (ECM), where the cointegrating relationship between the levels of the variables appears as the long-run equilibrium part of the equation. To allow for the presence of contemporaneous values of other endogenous variables on the right-hand side of an equation (for example, where the current real wage is a determinant of employment), this equation needs to be estimated by a method that allows for this to avoid bias in the parameter estimates. In what follows, this issue is addressed through the use of instrumental variables (IV) estimation. Where appropriate, tests of these and other characteristics of the estimated equations are shown in the tables of empirical results.

All the variables used in this section were first tested for their order of integration.¹⁵ All the relevant variables were found to be nonstationary, although in certain cases, this result was not clear cut (Table 3). Subsequently, tests for the presence of cointegration among the levels of the variables that compare the long-run parts of the participation, employment, and wage equation, respectively, showed that each had one cointegrating vector. The subsequent estimation of the dynamic model equations then builds on this finding. The results for each equation are discussed in somewhat greater detail next.

Table 3.

Tests of Orders of Integration

Note: The 95 percent critical value is 3.45 for the Dickcy-Fuller (DF) statistic, and 3.46 for the Augmented Dickcy-Fuller (ADF) statistic.

Table 3.

Tests of Orders of Integration

	Levels		Differences
Variable	DF	ADF	DF	ADF
LFR	–1.2	–2.4	–6.1	–3.2
LEPW	–0.9	–2.2	–4.0	–2.6
WNET	–3.1	–3.2	–7.3	–2.2
LE	–0.9	–2.5	–4.3	–2.9
WGR	–2.5	–2.8	–7.7	–2.6
Y	–1.8	–2.6	–7.8	–3.6
G	–2.2	–2.4	–11.0	–4.6
LPR	–1.7	–2.3	–8.2	–3.4
WMIN	–1.8	–3.1	–10.9	–3.3
POILR	–1.8	–2.1	–9.8	–4.9

Note: The 95 percent critical value is 3.45 for the Dickcy-Fuller (DF) statistic, and 3.46 for the Augmented Dickcy-Fuller (ADF) statistic.

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Table 3.

Tests of Orders of Integration

	Levels		Differences
Variable	DF	ADF	DF	ADF
LFR	–1.2	–2.4	–6.1	–3.2
LEPW	–0.9	–2.2	–4.0	–2.6
WNET	–3.1	–3.2	–7.3	–2.2
LE	–0.9	–2.5	–4.3	–2.9
WGR	–2.5	–2.8	–7.7	–2.6
Y	–1.8	–2.6	–7.8	–3.6
G	–2.2	–2.4	–11.0	–4.6
LPR	–1.7	–2.3	–8.2	–3.4
WMIN	–1.8	–3.1	–10.9	–3.3
POILR	–1.8	–2.1	–9.8	–4.9

Note: The 95 percent critical value is 3.45 for the Dickcy-Fuller (DF) statistic, and 3.46 for the Augmented Dickcy-Fuller (ADF) statistic.

Labor Force Equation

It is reasonable to hypothesize that the labor force participation rate depends on the probability of obtaining employment and on the prevailing net wage rate. Policy variables may also affect the decision of individuals to join or leave the labor force. For example, minimum wages may induce some individuals to offer their services who might otherwise not find it worthwhile to seek employment. Similarly, the replacement ratio of the unemployment insurance system might increase participation by offering an incentive to stay on the unemployment rolls instead of dropping out of the labor force.

Systematic testing and reduction yielded the model shown in Table 4. In it, the labor force participation rate is positively correlated with the employment rate (or negatively correlated with the unemployment or nonemployment rate). In addition, the findings suggest that higher net wages encourage labor force participation. These variables were found to form a cointegrating set (the Johansen likelihood ratio test was 31.9 compared with a 95 percent critical value of 29.7, confirming the presence of at least one cointegrating vector). However, none of the policy variables considered in this study (social security benefits, social security taxes, direct taxes, real interest rates, minimum wages, or the replacement ratio of the unemployment insurance system) was found to have a significant effect on the labor force participation rate when they were added to the basic economic variables already considered. Only the replacement ratio of the unemployment insurance system comes close to being significant, but it entered the equation with a negative sign—a counterintuitive result—and so was discarded as a probable influence upon participation.

Table 4.

Labor Force Equation

(Dependent variable LFR; sample period 1970Q3–1991Q4)

Note: In all the reported results, figures in parentheses are t-statistics. Other summary statistics quoted are defined as follows: ${\chi }_1^2\left(\mathrm{.}\right)$ is a Lagrange multiplier test of residual correlation; ${\chi }_2^2\left(\mathrm{.}\right)$ is the Ramsey RESET test; ${\chi }_3^2\left(\mathrm{.}\right)$ is a test for normality of residuals; and ${\chi }_4^2\left(\mathrm{.}\right)$ is a test for hereroscedasticity. ${\chi }_5^2\left(\mathrm{.}\right)$ is Sargan’s test that the instruments are valid. Instruments used were lagged values of the right-hand-side variables.

Table 4.

Labor Force Equation

(Dependent variable LFR; sample period 1970Q3–1991Q4)

Level equation
Variable		Constant		Employment ratio (LERPW)		Real consumption wage(WNET)
LFR		–0.4		0.39		0.08
		(6.6)		(7.3)		(2.47)
Dynamic equation
Variable		Constant	∆LFR(-1)	∆LERPW	∆LERPW(-1)	∆WNET	ECM(-1)
∆LFR		0.034	0.52	0.58	–0.41	0.005	–0.09
		(2.73)	(5.8)	(9.3)	(5.4)	(0.3)	(2.7)
$R^2=0.6,{\chi }_1^2\left(4\right)=1.68,{\chi }_2^2\left(1\right)=0.3,{\chi }_3^2\left(2\right)=12.9,{\chi }_4^2\left(1\right)=8.0,{\chi }_5^2\left(1\right)=1.6$

Note: In all the reported results, figures in parentheses are t-statistics. Other summary statistics quoted are defined as follows: ${\chi }_1^2\left(\mathrm{.}\right)$ is a Lagrange multiplier test of residual correlation; ${\chi }_2^2\left(\mathrm{.}\right)$ is the Ramsey RESET test; ${\chi }_3^2\left(\mathrm{.}\right)$ is a test for normality of residuals; and ${\chi }_4^2\left(\mathrm{.}\right)$ is a test for hereroscedasticity. ${\chi }_5^2\left(\mathrm{.}\right)$ is Sargan’s test that the instruments are valid. Instruments used were lagged values of the right-hand-side variables.

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Table 4.

Labor Force Equation

(Dependent variable LFR; sample period 1970Q3–1991Q4)

Level equation
Variable		Constant		Employment ratio (LERPW)		Real consumption wage(WNET)
LFR		–0.4		0.39		0.08
		(6.6)		(7.3)		(2.47)
Dynamic equation
Variable		Constant	∆LFR(-1)	∆LERPW	∆LERPW(-1)	∆WNET	ECM(-1)
∆LFR		0.034	0.52	0.58	–0.41	0.005	–0.09
		(2.73)	(5.8)	(9.3)	(5.4)	(0.3)	(2.7)
$R^2=0.6,{\chi }_1^2\left(4\right)=1.68,{\chi }_2^2\left(1\right)=0.3,{\chi }_3^2\left(2\right)=12.9,{\chi }_4^2\left(1\right)=8.0,{\chi }_5^2\left(1\right)=1.6$

Note: In all the reported results, figures in parentheses are t-statistics. Other summary statistics quoted are defined as follows: ${\chi }_1^2\left(\mathrm{.}\right)$ is a Lagrange multiplier test of residual correlation; ${\chi }_2^2\left(\mathrm{.}\right)$ is the Ramsey RESET test; ${\chi }_3^2\left(\mathrm{.}\right)$ is a test for normality of residuals; and ${\chi }_4^2\left(\mathrm{.}\right)$ is a test for hereroscedasticity. ${\chi }_5^2\left(\mathrm{.}\right)$ is Sargan’s test that the instruments are valid. Instruments used were lagged values of the right-hand-side variables.

Employment Equation

As expected, employment is affected negatively by real producer wages and positively by a measure of output. In addition, there is a somewhat unusual result, in that an indicator of the fiscal weight of the social security system has a strong negative effect on employment. This effect might be expected to be intermediated through the real wage, with the social security variable tending to increase real gross wages, which in turn would reduce employment. This issue is discussed more fully below.

Table 5 shows the parameter estimates. Tests confirmed the presence of a single cointegrating vector in this set of variables (LR = 38.0 compared with 27.1 at the 95 percent level). As with the other equations presented in this paper, this specification was obtained by systematically testing and reducing a general model. A full set of policy variables was included initially, notably the real interest rate, oil prices, a measure of international competitiveness, the replacement ratio of the unemployment insurance system, and the minimum wage. None of these—with the exception of the social security burden—was found to have a significant influence.

Table 5.

Employment Equation

(Dependent variable LE; sample period 1970Q3-1991Q4)

Note: For definitions, see Table 4. Instruments used were lagged values of GDP, the labor force, and wages.

Table 5.

Employment Equation

(Dependent variable LE; sample period 1970Q3-1991Q4)

Level equation
Variable	Constant	Real product wage(WGR)		Output (Y)	Fiscal variable (G)
LE	1.6	-0.04		0.26	-0.46
	(14.4)	(1.7)		(10.9)	(7.4)
Dynamic equation
Variable	Constant	∆LE(-1)	∆WGR	∆Y	∆G	ECM(-1)
∆LE	0.24	0.57	-0.001	0.08	-0.06	-0.15
	(4.29)	(9.1)	(0.0)	(3.74)	(1.96)	(4.3)
$\begin{array}{cc}\begin{array}{cc}\begin{array}{cc}\begin{array}{cc}\begin{array}{cc}{R}^2=0.77,& {\chi }_1^2\end{array}\left(4\right)=1.38,& {\chi }_2^2\left(1\right)=1.5,\end{array}& {\chi }_3^2\left(2\right)=7.6,\end{array}& {\chi }_4^2\end{array}\left(1\right)=2.6,& {\chi }_5^2\end{array}\left(3\right)=0.8$

Note: For definitions, see Table 4. Instruments used were lagged values of GDP, the labor force, and wages.

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Table 5.

Employment Equation

(Dependent variable LE; sample period 1970Q3-1991Q4)

Level equation
Variable	Constant	Real product wage(WGR)		Output (Y)	Fiscal variable (G)
LE	1.6	-0.04		0.26	-0.46
	(14.4)	(1.7)		(10.9)	(7.4)
Dynamic equation
Variable	Constant	∆LE(-1)	∆WGR	∆Y	∆G	ECM(-1)
∆LE	0.24	0.57	-0.001	0.08	-0.06	-0.15
	(4.29)	(9.1)	(0.0)	(3.74)	(1.96)	(4.3)
$\begin{array}{cc}\begin{array}{cc}\begin{array}{cc}\begin{array}{cc}\begin{array}{cc}{R}^2=0.77,& {\chi }_1^2\end{array}\left(4\right)=1.38,& {\chi }_2^2\left(1\right)=1.5,\end{array}& {\chi }_3^2\left(2\right)=7.6,\end{array}& {\chi }_4^2\end{array}\left(1\right)=2.6,& {\chi }_5^2\end{array}\left(3\right)=0.8$

Note: For definitions, see Table 4. Instruments used were lagged values of GDP, the labor force, and wages.

In particular, higher real interest rates appear to have no measurable direct, adverse effect on employment. This result runs counter to the hypothesis that an anti-inflationary monetary policy is associated with higher unemployment, at least in the short run. However, real interest rates may be shown to affect investment and output, and so affect employment indirectly.

From a policy standpoint, the key conclusion would appear to be that labor demand is sharply dampened by an increase in the overall burden imposed by the social security system. This burden is measured by social security expenditure, which by definition is the sum of social security taxes and the financial balance of the social security system. This result raises several difficult questions. The first two are statistical, while the third concerns the economic interpretation of the result.

First, it is somewhat surprising that the effect of the social security system on employment is not fully captured by producer wages, which already include social security taxes. To investigate this point further, wages net of social security taxes were substituted for gross wages in the employment equation. The result was that the adverse effect of the social security variable on employment became even larger, while the size of the coefficient on wages dropped sharply. The overall size of the effect of the social security system on employment was thus unchanged. There is, according to this result, evidence of a larger (negative) effect on employment of social security payments than is captured by their effect on the gross real product wage alone.

Second, it might be hypothesized that causality runs in the opposite direction, from employment to social security spending. Indeed, when employment declines, as in a cyclical downturn, social security spending tends to increase. 1 However, much of the effect of the cycle on employment is already accounted for by the inclusion of GDP in the equation. Furthermore, the adverse and separate effect of social security spending on employment is still found if the social expenditure variable is adjusted for cyclical deviations of actual GDP from potential GDP.

If it is granted that the effect of social expenditure on employment is statistically robust, what is the channel through which it exercises its influence? In particular, economic theory provides little support for the notion that social security benefits have a direct effect on the hiring decisions of employers. One possible explanation is that the employment equation is not a labor demand equation: this follows from the definition that any equation for employment is also an equation for nonemployment.¹⁶ In the preceding section, the nonemployment rate was shown to depend strongly and positively on social expenditure. The economic rationale for this effect appears straightforward: higher benefits encourage workers to remain non-employed.¹⁷ This effect, which seems empirically well founded and rests on a plausible behavioral theory, will therefore also be reflected in the equation for employment.

Wage Equation

In the long run, wage developments in France appear to be accounted for mainly by increases in labor productivity, unemployment, and the minimum wage. Again, it was found that a cointegrating vector exists in this set (LR = 30.3 compared with a 95 percent critical value of 29.7). The results of estimating an ECM with this vector as its equilibrium term are shown in Table 6.

Table 6.

Wage Equation

(Dependent variables WGR, LPR; sample period 1970Q3-1991Q4)

Note: For definitions, see Table 4. Instruments used were lagged values of the labor force, the real oil price, unemployment, and the minimum wage.

Table 6.

Wage Equation

(Dependent variables WGR, LPR; sample period 1970Q3-1991Q4)

Level equation
				Minimum
		Unemployment rate		wage	Real oil price
Variable	Constant	(LUR)		(WMIN)	(POILR)
WGR - LPR	-1.27 (5.8)	-1.69 (2.63)		0.21 (1.97)	0.05 (5.5)
Dynamic equation
∆(WGR - LPR)	Constant	∆LUR	∆WMIN	∆POILR	ECM(-1)
	0.21 (6.17)	0.57 (2.05)	-0.04 (1.0)	0.01 (3.19)	-0.16 (6.17)
$R^2=0.39,x_1^2\left(4\right)=3.1,x_2^2\left(1\right)=0.0,x_3^2\left(2\right)=0.86,x_4^2\left(1\right)=0.76,x_5^2\left(2\right)=0.0$

Note: For definitions, see Table 4. Instruments used were lagged values of the labor force, the real oil price, unemployment, and the minimum wage.

View Table

Table 6.

Wage Equation

(Dependent variables WGR, LPR; sample period 1970Q3-1991Q4)

Level equation
				Minimum
		Unemployment rate		wage	Real oil price
Variable	Constant	(LUR)		(WMIN)	(POILR)
WGR - LPR	-1.27 (5.8)	-1.69 (2.63)		0.21 (1.97)	0.05 (5.5)
Dynamic equation
∆(WGR - LPR)	Constant	∆LUR	∆WMIN	∆POILR	ECM(-1)
	0.21 (6.17)	0.57 (2.05)	-0.04 (1.0)	0.01 (3.19)	-0.16 (6.17)
$R^2=0.39,x_1^2\left(4\right)=3.1,x_2^2\left(1\right)=0.0,x_3^2\left(2\right)=0.86,x_4^2\left(1\right)=0.76,x_5^2\left(2\right)=0.0$

Note: For definitions, see Table 4. Instruments used were lagged values of the labor force, the real oil price, unemployment, and the minimum wage.

The minimum wage appears to have a strong influence on real wages as a whole, tending to raise them above what can be accounted for by productivity and unemployment. This result stands in contrast to some earlier studies of the French labor market.¹⁸ However, the work of other authors supports the conclusion reached in the present paper. Bazen and Martin (1991) show that a higher minimum wage raises the cost of youth labor. Moghadam (1995) finds a direct effect of the minimum wage on the real wage. He notes that the proportion of individuals earning the minimum wage is particularly high for those who are less than 26 years old (35.5 percent of wage earners in 1992), which strongly suggests that the overall effect is transmitted through younger workers.

Finally, the unemployment rate is an indicator of outsider pressure in wage negotiations; higher unemployment tends to act as a constraint on the wage demands of insiders.¹⁹

Dynamic Analysis

This section presents an analysis of the aggregate dynamics of the labor market. A system consisting of the behavioral equations and the identities described in the previous section was used to conduct a variety of simulations.

A first set of simulations examined the effect on unemployment of both a permanent and a temporary shock to (increase in) labor demand. These shocks took the form of a change in the constant term of the employment equation equal to 1 percent of the equilibrium level of employment. A permanent shock of this type permanently lowers the unemployment rate by about 1¾ percentage points (see Chart 6). As may be seen, the adjustment of employment and the labor force—and hence of unemployment—to a new equilibrium is fairly rapid. The response of wages is considerably slower. The reaction of the system to a temporary shock is somewhat different: the labor force initially responds more strongly than does employment, reflecting the strong effect of higher employment on wages. Thus, the unemployment rate rises before settling back to its equilibrium value (Chart 7).

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France: Response of Labor Market to Permanent Labor Demand Shock

Source: IMF staff calculations.Note: Shock to labor demand equivalent to 1 percent of employment.1 Deviation from baseline; in percentage points.2 Employment in percent of working-age population.3 Labor force in percent of working-age population.4 Real producer wages; percentage deviation from baseline.

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France: Response of Labor Market to Temporary Labor Demand Shock

Source: IMF staff calculations.Note: Shock to labor demand equivalent to 1 percent of employment.1 Deviation from baseline; in percentage points.2 Labor force in percent of working-age population.3 Employment in percent of working-age population.4 Real producer wages; percentage deviation from baseline.

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The dynamic system was also used to simulate the effect on unemployment of a permanent change in the level of social protection. Chart 8 shows the impact on the unemployment rate of a 1 percentage point reduction in the social security tax and benefit ratios (these ratios are computed relative to gross income from dependent employment). There is some overshooting of the unemployment rate early on, reflecting a stronger short-term effect on labor force participation. In the longer run, the effect on employment predominates, and the unemployment rate declines by about 0.2 percentage point. The incidence of the reduction in social security taxes is mainly on workers: producer wages increase by only ½ of 1 percent in the long run, largely reflecting the lower equilibrium unemployment rate, while net consumption wages rise by more than 1½ percent.

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France: Response of Labor Market to Permanent Alleviation of Social Security Taxes and Expenditure

Source: IMF staff calculations.Note: Reduction in revenue and expenditure by 1 percent of gross income from dependent employment.1 Deviation from baseline; in percentage points.2 Employment in percent of working-age population.3 Labor force in percent of working-age population.4 Percentage deviation from baseline.

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The last simulation examined the effect of a permanent 10 percent reduction in the real minimum wage (Chart 9). Again, there is some overshooting of the unemployment rate. In the long run, however, employment rises substantially and the unemployment rate drops about ½ of 1 percentage point. As would be predicted by theory, a reduction in the minimum wage leads to a somewhat smaller decline in average wages (the elasticity appears to be in the neighborhood of ½).

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France: Response of Labor Market to Permanent Reduction of the Minimum Wage

Source: IMF staff calculations.Note: Reduction by 10 percent in real terms, relative to the baseline.1 Deviation from baseline; in percentage points.2 Employment in percent of working-age population.3 Labor force in percent of working-age population.4 Percentage deviation from baseline.

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Concluding Remarks

The dynamic analysis is revealing, suggesting that dynamic responses to external shocks in France are relatively quick. Unemployment gets close to equilibrium within two years, a much shorter time than it takes other European countries to recover from a similar shock.

This is not a standard finding. Barrell, Morgan, and Pain (1995), for example, report that, if anything, France shows more inertia than do the other major European countries. There are, however, reasons for believing the present results are more likely. The model in this paper reveals powerful effects on the level of employment from social security payments and on wages from the minimum wage provisions. These are characteristics of the French labor market that are not found elsewhere in Europe. Hence, the role for a persistent movement in unemployment away from its equilibrium (NAIRU) rate is that much less in France, and, concomitantly, the structural rate of unemployment appears to have risen more in France than elsewhere.

For policy, these findings suggest that the share of the public sector in the economy, which has grown rapidly in the last quarter century and is now one of the highest among the industrial countries, may need to be reduced. Cutting the tax and social security burden should stimulate labor demand. Lower taxes, along with less generous benefits, can also be expected to give those who are not employed a greater incentive to seek work. The results presented in this study also provide support for a substantial reduction in the real minimum wage. Over time, it would be possible to lower the real minimum wage simply by avoiding any further increase in nominal terms.

Of course, policy recommendations based on macroeconomic results must be supplemented by a more disaggregated, microeconomic analysis. For example, because unemployment in France is concentrated among low-skilled individuals, measures targeted at this group could be relatively more effective. Thus, an across-the-board reduction in the level of social protection may be neither necessary nor sufficient to reduce unemployment.²⁰ What presumably matters more is the high minimum level of social support, which is one of the principal determinants of the reservation wage. The level and comprehensiveness of welfare benefits are a key social choice, entailing a trade-off between the generosity of benefits, on the one hand, and employment objectives, on the other. The evidence in this paper suggests that, if unemployment is to be substantially reduced, the generous system of social protection must be trimmed. To be sure, more effective education and training as well as labor and product market liberalization are also called for as part of a comprehensive attack on the unemployment problem.