This paper seeks to evaluate monetary policy rules which generalize the rule proposed by Taylor (1993). In particular, we consider rules in which the Fed sets the Federal funds rate as a function of the history of inflation, output and the Federal funds rate itself. Even though this is not part of Taylor’s original formulation, we introduce the possibility that the Federal funds rate depends on the history of the funds rate itself in order to allow for interest-rate smoothing of the kind that appears to be an important feature of current Fed policy. We also consider the character of optimal policy, i.e., the policy that maximizes the utility of the representative agent, assuming unlimited information about the exogenous disturbances to the economy. We then compare optimal policy in this unrestricted sense with the best rule of the generalized-Taylor family.
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Although the shape of the wage-effort offer curves is altered slightly, the same basic patterns of change can be seen in the three periods this.


We have provided in this paper substantial evidence that the US labor market offers a set of wage-effort contracts, with effort measured by annual hours.

This curve is uncovered by estimating two equations using industry level data. One equation explains wages as a function of capital intensity and the other equation explains hours also as a function of capital intensity. By solving out the capital intensity from these two equations we form a wage-hour offer curve.
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The interactive terms make it difficult to clearly see the impact of rents and union status on wages and hours. To facilitate the discussion of these interaction terms, Table 3.11 displays the estimated impact of a one-percent increase in union participation and in industry rents separately for a labor-intensive industry and a capital-intensive industry. The impact of union status on weekly hours is very small in magnitude but on wages is significant. Not surprisingly, the presence of unions tends to raise wages in the capital-intensive sectors more than in the labor-intensive sectors. But up until 1985 unions seemed to have a negative effect on wages in labor-intensive industries.
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Keeping all these concerns in mind, the wage and hour regressions are re-estimated using the same functional forms as before but with three new variables; the percentage of employees with union status, the log of average education, and the measure of industry rents. The variable for percent female was not included in these regressions, as we believe that this is a supply side rather than a demand side variable. Also included were two interactive variables, between union status and capital intensity and between industry rents and capital intensity. These interaction terms allow for the greater market power that employees may have in capital-intensive industries. More info The inclusion of the interactive term between education and capital made the results highly unstable and increased the standard errors significantly, thus was dropped from the regressions.
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Industry rents are particularly difficult to measure. The NBER data provides a measure of value added. Theoretically this variable represents employee wages, other employee benefits such as social security which are not directly included in the wage bill14, ex-ante capital rental costs, industry rents if any, and finally firm-specific rents which accrue to the owners of the capital,
The coefficient a represents the per worker cost of non-wage benefits plus average rents, /3 represents the capital rental costs, and 8 is the rent residual. Since it is impossible to separate from the constant that part which represents average rents, we use only the estimated rent residuals smoothed over seven periods to form estimates of sectoral long run rents.
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We use the employment rate to define the cycle. As is evident in Figure 3.2, weekly hours leads the employment rate, a feature we attribute to a delay between an increase/reduction in product demand and the actual hiring/firing of workers. To capture the cycle in demand, we use the smoothed forward rate of employment as the indicator of the business cycle, and we compare peak to peak and trough to trough changes in the wage-effort offer curve. Using smoother year-ahead rate of employment again as our guide we set our trough years as 61-62, 70-71, 75-76, 81-82, and 91-92. The peak years were set at 58-59, 67-68, 72-73, 77-78, 88-89 and 93-94. The results of these peak and trough regressions are displayed in Table 3.7 review.
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This twisting of the curve of observed wage-effort offers is not compatible with a representative worker model with a stable utility function since the contracts in the capital-intensive sectors have unambiguously improved while those in the labor-intensive sectors have unambiguously deteriorated. This twisting of the curve could be an equilibrium if workers have heterogeneous preferences. Differences in adversity to effort may also explain a portion of the apparent rigidity of the labor market to changes in relative wages across sectors: despite the shift in the wage-effort offer curve, the distribution of production workers across sectors has remained fairly stable. This is illustrated in Table 3.6 which reports employment by quintile of capital intensity. The sectors with the lowest capital/labor ratios experienced an 8.5% reduction in employment between 1970 and 1980. The third and fourth quintiles experienced the greatest gains while there was actually a decline in employment in the most capital-intensive sectors.
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The wage-effort offer curves in Figure 3.6 for 1960 and 1965 show the distinct backward bending form of the wage-effort that was evident in the two-digit data in Figure 3.2. The lowest curve in Figure 3.5 is the wage-effort offer curve in 1960. Between 1960 and 1970 two changes appear to be happening. First the backward bending portion of the wage-effort curve has been diminishing, possibly due to the decline in the power that unions had which allowed them to negotiate favorable contracts in the early sixties. In addition, the entire curve has been shifting up and to the right review.

Table 3.3:
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