## 1. How Might ALMPs Affect Employment?

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---

### I. Introduction
- Context:
  - Steady rise in unemployment rates in the 1970s and 1980s in Europe attributed to mismatches between labor skills demanded and supplied; excessive wages vis-à-vis productivity levels; over-generous out-of-work benefits; and rigid institutions reducing labor churning.
  - Policy response grouped under “active labor market policies” (ALMPs).
- Empirical summary (as stated):
  - Positive correlation between spending on ALMPs as a percentage of GDP and the employment rate in the business sector in the 1990s, but not in the late 1980s, when such expenditure was still relatively small.
  - Among ALMPs, direct subsidies to job creation were the most effective in raising employment rates; expenditures on training programs seem largely ineffective.
  - Estimation of a wage-setting curve shows substantial wage moderation associated with increases in ALMPs in the 1990s.
  - ALMPs increase employment but impose heavy fiscal costs; institutional reforms to lower production costs and enhance labor market flexibility and work incentives are suggested as better ways to increase employment rates.
- Methodological advances over previous studies:
  - Focus on employment rate (business sector) rather than unemployment.
  - Use of panel methods with within-country variation and data beyond 1995.
  - Explicit attention to reverse causality and institutional controls.

### II. Mechanisms: Why ALMPs May Affect Employment
- Five channels described within a labor demand / wage-setting framework:
  1. Better matching (training, active employment agencies) → smaller vacancies/unemployment ratio → downward shift in wage-setting curve and outward shift in labor demand → tend to raise employment; ambiguous final effect on real wages.
  2. Higher labor force productivity (training or on-the-job learning, spillovers) → upward shift in labor demand → raises employment and wages.
  3. Stronger labor force attachment (keeping unemployed workers connected) → downward shift in wage-setting curve → raises employment and reduces wages.
  4. Job creation programs may produce windfall substitution for nonsubsidized employment (reducing net effect), but income effects from lower labor costs could increase labor demand → could raise wages and employment in equilibrium.
  5. ALMPs may lower the disutility of being unemployed (provide occupation, income, skills) → workers demand higher wages in bargaining → could lower equilibrium employment.
- Caveat:
  - Even if ALMPs raise employment, fiscal cost may be very high, questioning overall effectiveness in a general equilibrium or cost–benefit sense.

### III. Identification Issues and Critique of Previous Studies
- Common flaws in prior cross-country aggregated studies:
  - Inability to separate role of labor market institutions from role of policies; need for panel data.
  - Small sample sizes and insufficient time variation in ALMPs.
  - Instability depending on metric used for ALMPs.
  - Reverse causality: movements in employment/unemployment induce changes in ALMP expenditures.
  - Focus on unemployment rates → overestimation of ALMP returns on employment and neglect of labor force participation effects.
- Specific methodological concerns:
  - Early cross-sectional studies (around 20 observations) risk attributing unobserved institutional features to ALMP spending.
  - Using ALMP expenditure per unemployed can bias results if ALMP spending rises less than proportionally with unemployment.
- Observed raw correlations (average 1985–2000) reported in figures:
  - ALMP/GDP = 0.03 - 0.04 * ER; t-statistics (2.63) (1.87).
  - PLMP/GDP = 0.06 - 0.08 * ER; t-statistics (2.78) (1.99).
  - ALMP/GDP = 0.28 + 0.36 * PLMP/GDP; t-statistics (1.45) (3.52).
- Additional points:
  - Larger cyclicality of PLMP expenditures casts doubt on measures like ALMP expenditure as a share of total labor market expenditure.
  - Focus on unemployment excludes program participants from unemployment statistics (bias when subsidies to private employment are included among ALMPs).
  - Few studies focus on business sector employment rates.

### IV. Empirical Identification and Data
- Key design choices:
  - Dependent variable: business sector employment rate = share of the working-age population employed in the business sector.
  - Normalization: ALMP expenditures measured as share of GDP (not per unemployed).
  - ALMP expenditures defined as sum of expenditures as a share of GDP on:
    - public employment services and administration
    - labor market training
    - youth measures
    - subsidized employment
    - measures for the disabled
  - Alternative specifications: excluding measures for the disabled; including each policy measure separately.
- Data:
  - Complete data for 15 industrial countries between 1985 and 2000.
  - Countries: Australia, Austria, Belgium, Canada, Denmark, Finland, France, Germany, Netherlands, Norway, New Zealand, Spain, Sweden, United Kingdom, United States.
  - Source: OECD Labor Market Policies database (described in Appendix I).
- Benchmark reduced-form specification:
  - BE_it = β1 ALMP_it + β2 X_it + β3 Y_t + β4 C_i + ε_it
    - BE = business sector employment rate; ALMP = ALMP expenditure (share of GDP); X = controls; Y = year dummies; C = country fixed effects.

### V. Estimates: Aggregate and Split-Sample Results
- Aggregate-sample (1985–2000):
  - No significant correlation between ALMP expenditures and business employment rates.
  - Reported coefficient: -0.13 with t-statistic -0.21 (Table 1, column (1)).
- Split-sample:
  - 1985–1992: ALMP coefficient = -0.12, not significant (Table 1, column (2)).
  - 1993–2000: ALMP coefficient = 1.88, highly significant (Table 1, column (3)).
    - Interpretation: for 1993–2000, a 1 percentage point increase in ALMP spending (as a share of GDP) is associated with an increase in the business employment rate of 1.9 percentage points.
- Benchmark and selected robustness estimates (preserve exact reported values):
  - Benchmark (1993–2000) ALMP Exp. coefficient: 1.88 (4.08) (Table 1 and Table 2, column (1)).
  - 1985–2000 ALMP Exp.: -0.13 (-0.21) in full-sample OLS (Table 1, column (1)).
  - 1985–1992 ALMP Exp.: -0.12 (-0.14) (Table 1, column (2)).
  - 1993–2000 excluding passive policies: ALMP Exp. = 1.36 (3.07) (Table 3, column (1)).
  - 1993–2000 excluding Nordic countries: ALMP Exp. = 2.62 (4.06) (Table 3, column (4)).
  - 1993–2000 excluding Anglo-Saxon countries: ALMP Exp. = 2.60 (3.42) (Table 3, column (5)).

### VI. PLMPs, Controls, and Consistent Patterns
- PLMP (passive labor market policy) expenditures:
  - PLMP Exp. consistently negative across periods.
  - Example values:
    - PLMP Exp. = -2.67 (-8.33) for 1985–2000 (Table 1, column (1)).
    - PLMP Exp. = -0.74 (-8.33) for 1993–2000 (Table 1, column (3)).
    - PLMP Exp. = -2.59 (-8.93) in a robustness specification (Table 3, column (4)).
- Control variables with consistent signs (selected examples preserve exact values where provided):
  - Technological growth: negative (examples: -0.13 (-2.36); -0.17 (-3.09); -0.17 (-2.93)).
  - Log GDP Business (per capita): positive (examples: 0.10 (4.11); 0.14 (4.80); 0.13 (4.75)).
  - Openness, replacement rate, union membership, tax wedge, and central bank independence tend to be negative in many specifications.
  - Share Public Empl., bargaining coordination, and employment protection change signs depending on period.

### VII. Detailed Breakdown of ALMP Components
- Main drivers of positive ALMP effect in the 1990s: direct subsidies to employment creation and measures for the disabled.
- Selected component estimates (from Table 4 and discussion; preserve reported values and signs):
  - PES (Public employment services and administration): negative association in some specifications (e.g., PES = -8.48 (-1.21) in 1985–1992 Table 4, column (1); PES = -6.51 (-2.63) in 1993–2000 Table 4, column (3)).
  - Labour Market Training: generally near zero or insignificant (examples: -0.49 (-0.26); 0.18 (0.08)).
  - Youth Measures: mixed or negative (examples: 1.12 (0.23); -3.52 (-1.98); 2.08 (0.88)).
  - Subsidized Employment (direct subsidies): positive and sometimes significant (examples: 1.28 (0.64); 3.68 (3.75) in 1993–2000 Table 4, column (3); 3.33 (2.87) in column (4)).
  - Measures for the disabled: mixed but sometimes positive (examples: 3.67 (0.47); 16.44 (1.25); 3.11 (2.21)).
- Dynamic/lags:
  - Lagged subsidized employment significant in dynamic specifications: Lagged Subsidized Employment = 6.91 (2.71) (Table 4, column (2)).

### VIII. ALMPs and Wage-Setting Behavior
- Estimated wage curve specification:
  - log(BW_it/P_it/A_it) = α1 log u_it + α2 ALMP_it + α3 X_it + α4 Y_t + α5 C_i + η_it.
- Wage elasticity to unemployment:
  - Exactly -0.1 in multiple specifications (examples: -0.10 (-4.53) for 1985–2000 Table 5, column (1); -0.10 (-5.73) for 1993–2000 Table 5, column (3)).
- ALMP effects on wages (selected reported coefficients):
  - 1985–2000: ALMP Exp. = -6.19 (-1.99) (Table 5, column (1)).
  - 1993–2000: ALMP Exp. = -6.62 (-4.37) (Table 5, column (3)).
  - IV and other corrections: ALMP Exp. = 5.30 (0.46) in one IV specification and -7.52 (-4.63) in another (Table 5, columns (4) and (5)).
- Lagged ALMPs:
  - Including lagged ALMPs leaves main wage-setting results insensitive (Table 6, column (2) Lagged ALMP Exp. = 1.02 (-0.56) and ALMP Exp. = -5.91 (-3.41)).
- Within-component wage effects (Table 6, column (3)):
  - PES: positive and significant (26.59 (2.75)), indicating PES and youth measures can shift the wage-setting curve upwards.
  - Labour Market Training: reported negative in detailed ALMP wage regression (10.33 (-3.51) listed with negative implication in table layout).
  - Subsidized Employment: negative (example: -5.80 (-2.33)), indicating contribution to wage moderation.
  - Measures for the disabled: mixed; specification shows e.g., -44.98 (-1.92) in a detailed cell.
- Composition effect concern:
  - Direct subsidies targeted to low-paid workers could reduce average wages through a composition effect, potentially generating a spurious link between ALMPs and wage moderation.

### IX. Additional Findings and Robustness Notes
- Additional reported findings:
  - ALMPs have a positive effect on labor force participation.
  - Larger effect of ALMPs on total employment rates (partly mechanical via public sector employment).
  - Employment protection indices for regular and temporary employment produced similar results when used separately.
  - The ALMP coefficient increases when government current receipts (as a share of GDP) are included.
  - The ratio of minimum to median wages does not affect equilibrium employment rates in most specifications.
- Reverse causality and controls:
  - Excluding PLMPs reduces the ALMP coefficient from 1.88 to 1.36 (Table 3, column (1)), but the main positive ALMP result persists in many specifications.

### X. Policy Implications and Final Remarks
- Main empirical conclusion:
  - ALMPs appear effective, on average, in raising employment rates in the business sector of 15 industrial countries in the 1990s; direct subsidies to job creation seemed most effective.
- Wage moderation:
  - ALMP increases were correlated with less real wage growth after controlling for technological growth, unemployment, and institutional/economic factors; wage moderation may have contributed to employment improvements.
- Cost-effectiveness and limits:
  - ALMP budgetary cost is high and subject to diminishing returns as employment rates rise.
  - ALMPs could recoup costs if benefit recipients are placed into jobs and benefits phased out, but this neglects social benefits of lowering unemployment.
- Preferred policy direction:
  - Given negative effects of current institutional arrangements on European employment, institutional reforms are preferred to improve labor utilization without high societal costs.
  - Suggested institutional reform directions based on estimated coefficients:
    - Reductions in tax wedges.
    - Reductions in benefits replacement rates.
    - Reductions in public sector employment.
    - Reductions in insiders’ wage bargaining power.

*Source: _wp03234 - 1. How Might ALMPs Affect Employment?*

### 1. How Might ALMPs Affect Employment?.......................................................................5

### 1. How Might ALMPs Affect Employment?

### I. Introduction
- Steady rise in unemployment rates in the 1970s and 1980s in Europe has been attributed to: mismatches between labor skills demanded and supplied; excessive wages vis-à-vis productivity levels; over-generous out-of-work benefits; and rigid institutions reducing labor churning.
- Policy response grouped under “active labor market policies” (ALMPs).
- Empirical summary of paper findings (as stated):
  - Positive correlation between spending on ALMPs as a percentage of GDP and the employment rate in the business sector in the 1990s, but not in the late 1980s, when such expenditure was still relatively small.
  - Among ALMPs, direct subsidies to job creation were the most effective in raising employment rates; expenditures on training programs seem largely ineffective.
  - Estimation of a wage-setting curve shows substantial wage moderation associated with increases in ALMPs in the 1990s.
  - ALMPs increase employment but impose heavy fiscal costs; institutional reforms to lower production costs and enhance labor market flexibility and work incentives are suggested as better ways to increase employment rates.
- Methodological advances claimed over previous studies:
  - Focus on employment rate (business sector) rather than unemployment.
  - Use of panel methods with within-country variation and data beyond 1995.
  - Explicit attention to reverse causality and institutional controls.

### II. Why Might ALMPs Increase Employment?
- Five channels through which ALMPs may affect employment (described using a simple labor demand / wage-setting framework):
  1. Better matching between vacancies and job-seekers (e.g., training, active employment agencies) → smaller vacancies/unemployment ratio → downward shift in wage-setting curve and outward shift in labor demand → tend to raise employment; ambiguous final effect on real wages.
  2. Higher labor force productivity (training or on-the-job learning, spillovers) → upward shift in labor demand → raises employment and wages.
  3. Stronger labor force attachment (keeping unemployed workers connected) → downward shift in wage-setting curve → raises employment and reduces wages.
  4. Job creation programs may produce windfall substitution for nonsubsidized employment (reducing net effect), but income effects from lower labor costs could increase labor demand → could raise wages and employment in equilibrium.
  5. ALMPs may lower the disutility of being unemployed (provide occupation, income, skills) → workers demand higher wages in bargaining → could lower equilibrium employment.
- Important caveat: even if ALMPs raise employment, fiscal cost may be very high, questioning overall effectiveness in a general equilibrium or cost–benefit sense.

### III. Identification Issues and Critique of Previous Studies
- Common flaws in prior cross-country aggregated studies:
  - Inability to separate role of labor market institutions from role of policies; need for panel data.
  - Small sample sizes and insufficient time variation in ALMPs.
  - Instability depending on metric used for ALMPs.
  - Reverse causality: movements in employment/unemployment induce changes in ALMP expenditures.
  - Focus on unemployment rates → overestimation of ALMP returns on employment and neglect of labor force participation effects.
- Specific methodological concerns:
  - Early cross-sectional studies (around 20 observations) risk attributing unobserved institutional features to ALMP spending.
  - Later panel studies often pool data or average ALMP expenditures to reduce reverse causality, which neglects time variation useful for identification.
  - Using ALMP expenditure per unemployed can bias results: if ALMP spending rises less than proportionally with unemployment, apparent negative relationship between ALMP/unemployment ratio and unemployment rate can result.
- Observed raw correlations (average 1985–2000):
  - ALMPs/GDP negatively correlated with business employment rate in raw cross-country plots, likely reflecting reverse causality.
  - PLMPs (passive labor market policies: unemployment compensation and early retirement for labor market reasons) show a stronger negative correlation with employment rates than ALMPs, likely mechanical linkage (lower employment → higher unemployment compensation outlays).
  - ALMP/GDP = 0.03 - 0.04 * ER; reported t-statistics (2.63) (1.87) shown in figure annotations.
  - PLMP/GDP = 0.06 - 0.08 * ER; reported t-statistics (2.78) (1.99).
  - ALMP/GDP = 0.28 + 0.36 * PLMP/GDP; reported t-statistics (1.45) (3.52).
- Additional points:
  - Larger cyclicality of PLMP expenditures casts doubt on measures like ALMP expenditure as a share of total labor market expenditure.
  - Focus on unemployment excludes program participants from unemployment statistics (creating bias when subsidies to private employment are included among ALMPs).
  - Many studies do not focus on employment rates in the business sector; none of the reviewed studies, to the author’s knowledge, focuses on business sector employment rates.

### IV. Empirical Identification of the Effect of ALMPs on Employment Rates
- Key design choices to address shortcomings:
  - Dependent variable: share of the working-age population employed in the business sector (business sector employment rate). Rationale:
    - Accounts for labor force participation effects of ALMPs.
    - Excludes cyclical increases in public sector employment that do not reflect productivity or cost improvements.
    - Employment rate is a better measure of utilization of able-to-work individuals than unemployment.
  - Normalization: ALMP expenditures measured as share of GDP (not per unemployed) to avoid upward bias from reverse causality; author notes this may bias estimates downward via spurious negative correlation with aggregate output shocks.
  - ALMP expenditures definition (sum of expenditures as a share of GDP on):
    - public employment services and administration
    - labor market training
    - youth measures
    - subsidized employment
    - measures for the disabled
  - Alternative specifications considered: excluding measures for the disabled; including each policy measure separately.
- Data:
  - Complete data available for 15 industrial countries between 1985 and 2000.
  - Countries: Australia, Austria, Belgium, Canada, Denmark, Finland, France, Germany, Netherlands, Norway, New Zealand, Spain, Sweden, United Kingdom, United States.
  - OECD Labor Market Policies database described in Appendix I.
- Econometric interpretation:
  - Estimated equation is a reduced form determining employment rates and wages.
  - Wages are excluded from the employment rate specification; estimated effect of ALMPs on employment should incorporate shifts in wage-setting indirectly.
- Benchmark equation structure (as presented):
  - BE_it = β1 ALMP_it + β2 X_it + β3 Y_t + β4 C_i + ε_it
    - where BE = business sector employment rate; ALMP = active labor market policy expenditure (share of GDP); X = control variables; Y = time effects; C = country fixed effects.
- Sample and data period explicitly emphasized: 1985–2000, 15 countries.

*Source: _wp03234 - 1. How Might ALMPs Affect Employment?*

### Appendix I.

### Appendix I.

### Model specification
- Dependent and explanatory variables:
  - BE is business employment as a share of the working-age population.
  - ALMP is spending on active labor market policy (as a share of GDP).
  - X is a vector of control variables capturing changes in institutions and the business cycles.
  - Y is a vector of year dummies to control for common shocks.
  - C is a vector of country dummies.
  - ε is the error term.
- Time and country dummies are emphasized as very important components of the specification:
  - Time dummies may alleviate reverse causality if the timing of adverse shocks is correlated between countries.
  - Country fixed effects capture all time-invariant institutional and economic features that explain cross-country differences in employment rates.
  - The text illustrates the importance of country-specific effects with Luxembourg and Belgium: since the mid-1980s, Belgium spent on average 1.2 percent of GDP on ALMPs and Luxembourg 0.2 percent, yet Luxembourg had a higher business sector employment rate in the sample period (66 percent compared to 45 percent for Belgium).

### Control variables and identification strategy
- Control variables:
  - The logarithm of per capita GDP in the business sector (in 1995 prices) to capture the level of economic activity.
  - Technological growth and the extent of economic openness.
  - The share of GDP spent on PLMPs (passive labor market policies), included because of its positive raw correlation with expenditures on ALMPs and to capture common cyclical factors.
  - Institutional variables with time variation (described in Appendix II).
  - Other commonly used controls (real long-term interest rates, ratio of minimum to median wages, and other institutional variables) were considered but excluded from the final specification because their effect on employment rates was not significantly different from zero.
- Identification and endogeneity concerns:
  - The conditional correlation between employment and ALMP expenditure could be driven by a third omitted variable affecting both ALMP expenditures and employment.
  - Calmfors and Skedinger (1995) propose instruments for ALMP spending, but it is argued that those instruments are unlikely to affect unemployment only through ALMP.
  - Lagged values of expenditures on ALMPs were used as instrumental variables for current expenditures in some specifications and did not change the results.
  - Other specifications used lagged expenditures on ALMPs as regressors (instead of instruments) to check for dynamic effects.

### Estimates of the effect of ALMPs on the employment rate
- Aggregate-sample result:
  - For the whole sample period, there is no significant correlation between ALMP expenditures and business employment rates (Table 1, column (1): coefficient of -0.13 with a t-statistic of -0.21).
- Split-sample results:
  - 1985-1992 sub-sample (Table 1, column (2)): coefficient on ALMP spending is -0.12 and not significantly different from zero.
  - 1993-2000 sub-sample (Table 1, column (3)): coefficient on ALMP spending is 1.88 and highly significant.
    - Interpretation provided: for the 1993–2000 sub-sample, a 1 percentage point increase in ALMP spending (as a share of GDP) is associated with an increase in the business employment rate of 1.9 percentage points.
- Robustness:
  - Various specifications of the model (referenced as Tables 1 to 4) confirm the pattern of ALMP effectiveness in the 1990s but not before then.
  - Use of lagged ALMP expenditures as instruments or as regressors did not change the qualitative results.

*Appendix I.*

### introduction of a lag in the measure of expenditures in ALMPs to check for dynamic effects

### introduction of a lag in the measure of expenditures in ALMPs to check for dynamic effects

### Dynamic effects and robustness checks
- Introducing a lag in the measure of expenditures in ALMPs shows a cumulative positive effect during 1993-2000 and insignificant effects in the earlier period (Table 1, columns (4) and (5)).
- Modifications in the cutoff point dividing the two periods (Table 2, columns (2) and (3)) and only using lagged expenditures on ALMPs or on PLMPs as the relevant policy variables (Table 2, columns (4) and (5)) do not change the results.
- Using Feasible GLS with different assumptions about residual serial correlation and heteroscedasticity broadly leaves results unchanged; OLS results were presented for transparency and replication.
- Country dummies are important to the positive coefficient estimate for ALMPs (Table 3, column (3)); excluding particular groups of countries does not alter basic results (Table 3, columns (5) to (7)).
- Exclusion of Nordic countries augments the estimated coefficient of ALMP expenditures to 2.6 (Table 3, column (4) entry ALMP Exp. = 2.62 (4.06)), consistent with prior studies.

### ALMPs and employment outcomes (benchmark estimates and sensitivity)
- Benchmark (1993-2000) ALMP Exp. coefficient: 1.88 (4.08) (Table 1 and Table 2, column (1)).
- Alternative period and specification estimates (selected):
  - 1985-2000 ALMP Exp.: -0.13 (-0.21) in full-sample OLS (Table 1, column (1)).
  - 1985-1992 ALMP Exp.: -0.12 (-0.14) (Table 1, column (2)).
  - 1993-2000 ALMP Exp. (Table 1, column (3)): 1.88 (4.08).
  - 1993-2000 excluding passive policies (Table 3, column (1)) ALMP Exp.: 1.36 (3.07).
  - 1993-2000 excluding Nordic countries (Table 3, column (4)) ALMP Exp.: 2.62 (4.06).
  - 1993-2000 excluding Anglo-Saxon countries (Table 3, column (5)) ALMP Exp.: 2.60 (3.42).
- PLMP Exp. consistently negative across periods:
  - Example values: PLMP Exp. = -2.67 (-8.33) for 1985-2000 (Table 1, column (1)); PLMP Exp. = -0.74 (-8.33) for 1993-2000 (Table 1, column (3)); Table 3 shows PLMP Exp. = -2.59 (-8.93) in one robustness specification (column (4)).
- Control variables with consistent signs:
  - Technological growth: negative (examples: -0.13 (-2.36); -0.17 (-3.09); -0.17 (-2.93)).
  - Log GDP Business (per capita): positive (examples: 0.10 (4.11); 0.14 (4.80); 0.13 (4.75)).
  - Openness, replacement rate, union membership, tax wedge, and central bank independence tend to be negative in many specifications.
  - Share Public Empl., bargaining coordination, and employment protection change signs depending on period.

### Detailed breakdown of ALMPs (Table 4)
- Direct subsidies to employment creation and measures for the disabled appear to be the main drivers of the positive ALMP effect on employment in the 1990s.
- Specific component estimates (selected values from Table 4 and discussion):
  - PES (Public employment services and administration): negative association with employment in some specifications (e.g., PES coefficient -8.48 (-1.21) in 1985-1992, Table 4, column (1); PES = -6.51 (-2.63) in 1993-2000, Table 4, column (3)).
  - Labour Market Training: generally near zero or insignificant (examples: -0.49 (-0.26); 0.18 (0.08)).
  - Youth Measures: mixed or negative (examples: 1.12 (0.23); -3.52 (-1.98); 2.08 (0.88)).
  - Subsidized Employment (direct subsidies): positive and sometimes significant (examples: 1.28 (0.64); 3.68 (3.75) in 1993-2000, Table 4, column (3); 3.33 (2.87) in column (4)).
  - Measures for the disabled: mixed but sometimes positive (examples: 3.67 (0.47); 16.44 (1.25); 3.11 (2.21)).
- Lagged components: lagged subsidized employment shows significance in dynamic specifications (Table 4, column (2) Lagged Subsidized Employment = 6.91 (2.71)).
- Excluding the same country groups as in Table 3 does not change the breakdown results (not shown).

### ALMPs and wage-setting behavior (wage curve estimates)
- Estimated wage curve specification: log(BW_it/P_it/A_it) = α1 log u_it + α2 ALMP_it + α3 X_it + α4 Y_t + α5 C_i + η_it (as described in text).
- ALMPs are associated with wage moderation throughout the sample; estimates for the first half are not significantly different from zero (Table 5).
- Estimated elasticity of wages to the unemployment rate: exactly -0.1 in multiple specifications (examples: -0.10 (-4.53) for 1985-2000 in Table 5, column (1); -0.10 (-5.73) for 1993-2000 in Table 5, column (3)).
- ALMP Exp. coefficients in wage regressions (selected):
  - 1985-2000: -6.19 (-1.99) (Table 5, column (1)).
  - 1993-2000: -6.62 (-4.37) (Table 5, column (3)).
  - IV and other corrections yield similar results (Table 5, columns (4) and (5): ALMP Exp. = 5.30 (0.46) in one IV specification and -7.52 (-4.63) in another).
- Including lagged ALMPs leaves main wage-setting results insensitive (Table 6, column (2) Lagged ALMP Exp. = 1.02 (-0.56) and ALMP Exp. = -5.91 (-3.41)).
- Within ALMP components for wages (Table 6, column (3)):
  - PES: positive and significant (26.59 (2.75)), indicating PES and youth measures shift the wage-setting curve upwards.
  - Labour Market Training: negative in detailed ALMP wage regression (10.33 (-3.51) listed as negative sign in table layout).
  - Subsidized Employment: negative (example: -5.80 (-2.33)), indicating contribution to wage moderation.
  - Measures for the disabled: mixed; some specifications show negative contributions to wages (e.g., -44.98 (-1.92) appears in a detailed cell).
- Composition effect concern: direct subsidies targeted to low-paid workers could reduce average wages through a composition effect, potentially generating a spurious link between ALMPs and wage moderation.

### Additional empirical findings and sensitivity notes
- Additional results not shown in main tables:
  - ALMPs have a positive effect on labor force participation.
  - A larger effect of ALMPs on total employment rates (partly mechanical via public sector employment).
  - Employment protection indices for regular and temporary employment produced similar results when used separately.
  - The coefficient of ALMP increases when government current receipts (as a share of GDP) are included.
  - The ratio of minimum to median wages does not affect equilibrium employment rates in most specifications.
- Reverse causality and controls:
  - PLMPs have a consistent negative effect on employment rates; part of this may represent reverse causality. Excluding PLMPs reduces the ALMP coefficient from 1.88 to 1.36 (Table 3, column (1)).
  - A more complete model could include an equation for PLMP expenditures; dynamic relationships between PLMP and ALMP disbursements could bias ALMP coefficients, but main positive ALMP result persists when PLMPs are excluded.

### Policy implications and final remarks
- Main empirical conclusion: ALMPs appear effective, on average, in raising employment rates in the business sector of 15 industrial countries; direct subsidies to job creation seemed most effective.
- ALMP increases were correlated with less real wage growth after controlling for technological growth, unemployment, and institutional/economic factors; wage moderation may have contributed to employment improvements.
- Cost-effectiveness remains undetermined: ALMP budgetary cost is high and subject to diminishing returns as employment rates rise; ALMPs could recoup costs if benefit recipients are placed into jobs and benefits phased out, but this neglects social benefits of lowering unemployment.
- Given negative effects of current institutional arrangements on European employment, institutional reforms are preferred to improve labor utilization without high societal costs.
- Suggested institutional reform directions based on estimated coefficients:
  - Reductions in tax wedges.
  - Reductions in benefits replacement rates.
  - Reductions in public sector employment.
  - Reductions in insiders’ wage bargaining power.

*Source: _wp03234 - introduction of a lag in the measure of expenditures in ALMPs to check for dynamic effects*

### References

### References

### References list

- Bellmann, L. and Jackman R., 1996, “The impact of Labour Market Policy on Wages, Employment and Labour Market Mismatch,” in Schmid G., O’Reilly J. and Schömann (eds), International Handbook of Labour Market Policy and Evaluation, pp. 725-746, Elgar, Cheltenham.  
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- Nickell, S. and R. Layard, 1999, “Labor Market Institutions and Economic Performance,” in O. Ashenfelter and D. Card (eds.), Handbook of Labor Economics, Elsevier Science.  
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*Source: _wp03234 - References*

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_Source: https://www.imf.org/-/media/websites/imf/imported-full-text-pdf/external/pubs/ft/wp/2003/_wp03234.pdf_