The Selected Issues paper provides an estimate of the output gap and potential output for Italy, and examines the sensitivity of the results to assumptions regarding employment and productivity growth. The paper focuses on the labor market more directly by examining the linkages between wage bargaining systems, regional wage differentiation, and regional unemployment disparities. It also provides an assessment of the government’s tax reform program, including its potential to increase incentives for employment and investment.

Abstract

The Selected Issues paper provides an estimate of the output gap and potential output for Italy, and examines the sensitivity of the results to assumptions regarding employment and productivity growth. The paper focuses on the labor market more directly by examining the linkages between wage bargaining systems, regional wage differentiation, and regional unemployment disparities. It also provides an assessment of the government’s tax reform program, including its potential to increase incentives for employment and investment.

II. New Estimates of Potential Output 1

A. Introduction

8. This chapter presents updated estimates of the output gap and potential growth for Italy, and compares these with those of the OECD, the EU Commission and the Italian authorities. Estimates of potential output play an important role in guiding the staff’s analysis and policy recommendations. The output gap combined with potential growth provide a measure of the scope for noninflationary growth over both the short and longer term. Estimates of the output gap also play a central role in assessing fiscal policy: the current stance and appropriate policy for the short term.

9. It is timely to update the estimates of potential output given that actual output growth has been relatively low over recent years. Previous staff estimates (using data up to 1996) had suggested that over the late 1990s potential output growth was around 1.9 percent per year,2 that actual output was well below potential—by as much as 2.7 percent in 1999—and hence, that growth of more than 2 percent for a number of years was required to close this gap. However, actual growth averaged only 2 percent from 1997 to 2001 (and 1.6 percent over the past decade).

10. Indeed, new estimates of potential output suggest that the output gap and potential growth were somewhat lower over the past few years than suggested by previous staff estimates. The new estimates of the output gap are in line with the latest estimates from the EU Commission, OECD, and the Italian authorities, while new estimates of future potential output growth (at around 2 percent per year) are considerably lower than those of the OECD and the Italian authorities.

11. A key feature of output growth over recent years has been the decline in productivity growth (both labor and total factor productivity, TFP), coupled with a substantial rise in employment growth (Figure 1). Higher employment growth has more recently offset the decline in TFP growth, so that potential output growth has now recovered to around 2 percent. These developments raise two key questions relating to future potential output growth. First, what are the prospects for employment growth? Second, what are the prospects for a reversal of the trend decline in TFP growth? In answer to the first question, it appears that without additional and far-reaching measures to liberalize labor markets, employment growth is likely to moderate—bringing its growth rate down to its historical average (relative to GDP). The answer to the second question draws on the historical experience for Italy, as well as that of selected European countries. This suggests that a rebound in the rate of productivity growth is likely, helped perhaps by a moderation of employment growth.

Figure 1.
Figure 1.

Employment Growth and Labor Productivity, 1980–2001

Citation: IMF Staff Country Reports 2002, 232; 10.5089/9781451819830.002.A002

Sources: For sources here, and elsewhere, see Appendix I.

12. The chapter is organized as follows. The next section outlines the production function approach to estimating potential output. Section C presents the data, and discusses the likely future trends for TFP growth—drawing in part on cross-country comparisons of TFP growth over the past decade. Production function estimates of potential output are then presented, and compared with earlier staff estimates. Section D compares the new production function estimates of the staff with those of the OECD, the EU commission, and the Italian authorities, focusing especially on likely future trends in employment growth. Conclusions are drawn in Section E.

B. The Production Function Approach

13. The production function approach to estimating potential output starts with a production function linking output to labor and capital inputs, and total factor productivity (TFP).3 Potential output is calculated as the level of output that would arise when at full employment (that is, consistent with the nonaccelerating inflation rate and a “normal” level of labor force participation), when capacity utilization is at “normal” levels, and when TFP is at its trend level. Assuming a Cobb-Douglas production function, with constant returns to scale implies: 4

log(Yt)=alog(Lt)+(1a)log(Kt)+TFPt(1)

where: Y is real GDP; L and K are measures of labor and capital inputs respectively; and TFP is total factor productivity (see Appendix I for a description of the data). Assuming also competitive markets implies that a is equal to the (constant) labor share of income (which for Italy averaged 0.7 from 1980 to 2001).5 TFP can then be measured as the residual of equation (1).

14. There are a number of variations to this basic setup, attempting to measure factor inputs more precisely by adjusting for the intensity with which the input is used, and/or its effectiveness. The most basic measure of the labor input is simply the number of (full-time equivalent) employed persons, E. Alternatively, employment can be adjusted by the average hours worked per employee, as follows:

L=E×HW=(WP×pr)(1-u)HW(2)

where: WP is the working age population; pr is labor force participation rate; u is the unemployment rate; and HW is the average hours worked (per full-time equivalent employee).6 The breakdown of employment into the two bracketed terms in equation (2), is a convenient formulation for projecting future potential output because it allows changes in employment to be explicitly derived from the combination of changes in demographics, and labor force participation and unemployment rates.

15. Another possible adjustment is to account for the cyclical impact of the capacity utilization rate, util, which can be done directly as follows:

log(Y)=alog(L)+(1-a)log(K×util)+TFP(3)

Measures of capacity utilization—which are survey based—may also partially reflect the intensity with which labor is used, and typically refer only to the industrial sector. Therefore, it makes sense to examine a formulation that allows the coefficient on util to differ from that on capital. Though not reported here, results from such a formulation showed that the coefficient on util was not significantly different from (l-a), but it was significantly different from zero.7 It makes sense, therefore, to adopt the formulation shown in equation (3). Despite this adjustment, it appears that measured TFP remains relatively volatile (see below) and contains what appears to be a cyclical element, suggesting the need to smooth TFP in order to obtain a measure of trend or potential TFP growth.

16. Potential output is obtained by substituting “potential factor inputs” into equation (3), and replacing TFP with a measure of trend TFP. The potential capital stock is assumed to be the actual capital stock. For the labor input components: potential WP is taken to be the actual; a Hodrick-Prescott (HP) filter is applied to pr and hw; and the NAIRU is used in the place of u. Finally, an HP filter is also applied to util and to TFP.

17. The use of the HP filter in this fashion can be problematic because of the end-point problem, whereby trends at the end of the sample period are disproportionately affected by the most recent observations.8 This is especially noticeable during a period of rapid change in the variables of interest, which is the case for both TFP growth and participation since 1996. One way to overcome this is to artificially extend the sample period using projections of the variables in question.

C. Data Description, Trend TFP, and Potential Output

Data description

18. Data is annual from 1980 to 2001. For the purpose of applying HP filters beyond the current period, variables are projected out to 2007, which also corresponds to the current horizon of the IMF World Economic Outlook (WEO)—in fact, at least initially, projections are generally based on the most recent WEO. The implications of shorter horizons and of alternative projections are discussed in the results section below. Further details are provided in Appendix I.

19. Table 1 provides a summary of the relevant factor inputs, in terms of their growth rates, their contributions to actual output growth, and measured TFP growth (based on existing WEO projections for the period 2002-07). Of particular interest is the sharp decline in TFP growth in the late 1990s, coinciding with a strong reversal in the contribution of labor—from -0.5 percentage points from 1990-96, to 0.9 percentage points from 1997-2001. Also, while the current WEO projections imply a rebound in TFP growth, it remains considerably below its average prior to 1996. Before turning to the derivation of potential output, a series for potential TFP is required.

Table 1.

Summary Statistics—Annual Averages

article image
Sources: See Appendix I.

Staff estimates and projections.

Contributions are calculated by multiplying capital and labor factors by 0.3 and 0.7, respectively.

Potential TFP

20. To obtain trend or potential TFP, measured TFP needs to be stripped of possible cyclical and/or erratic components using either structural, or nonstructural estimation methods. The trend component may be either deterministic (as implied by neoclassical growth models) or may ultimately depend on the investment behavior of households, businesses and government (as suggested by theories of endogenous growth, with vintage capital, human capital, and/or research and development capital). Mc Morrow and Roeger (2001) present estimates based on a vintage capital stock model of TFP with a broken trend and the average age of the capital stock as explanatory variables; the cyclical or erratic component is captured by the residual.

21. An alternative, nonstructural approach to estimating trend TFP is to use an HP filter.9 This has the advantage of simplicity, but suffers from the end-point problem.10 This can be addressed by extending the sample period through the use of projections.11 While this necessarily introduces an element of subjectivity (that is, forecasting errors), the structural approach itself also suffers from this problem (arising through the choice of the structural model), as well as the end point problem (to the extent that it still relies on some form of deterministic trend, as in Mc Morrow and Roeger, 2001).

22. While there has been a sharp slowdown in TFP growth in Italy since 1997, there are a number of reasons why this is not expected to continue. This would make the end-point problem associated with the HP filter especially problematic at the current juncture. Several developments could explain the decline in measured TFP growth from 1997 to 2001, and suggest that it might be reversed in the future:

  • Foremost is the rapid growth of employment since 1997.12 Employment growth may have altered the composition of the workforce, thereby influencing TFP growth as measured by the simple production function used here—that is, one that treats workers and jobs as homogeneous. In order to examine the implications of compositional change in the workforce for measured TFP growth, there are at least three cases worth considering:

  • (i) The first case assumes (not unreasonably) that education (outside of the workplace) leads to more productive workers. In this case, the average productivity of the workforce would have risen steadily over time in line with the increase in the average years of schooling per person in Italy. Brandolini and Cipollone (2001) account for this by scaling the labor input by an index of the average years of schooling of the workforce. This implies, however, that measured TFP growth is consistently lower over the whole sample period than implied by the estimates presented above (since years of schooling has increased in a linear fashion over time). In other words, this phenomenon cannot explain the sudden decline in measured TFP growth after 1997.

  • (ii) The second case assumes that on-the-job training and experience increase a worker’s productive abilities. In this case, a surge in newer, and hence inexperienced workers, would lead to a reduction in the average productivity of the workforce—as seems to have been the case since 1997, especially given the sharp decline in unemployment. In this respect, the experience of Italy over this period appears to have been quite similar to that of the Netherlands, where there was a large fall in measured TFP growth—by 1 percentage point on average from 1990-96 to 1997-2001 (Table 2—at the same time as average annual employment growth rose sharply—from 1.8 to 2.8 percent. Looking ahead, two factors are likely to work to raise the average quality of the pool of employed persons in Italy. First, employment growth is projected by staff to almost halve, from an average annual rate of around 1.3 percent from 1997 to 2001 (and as high as 2.0 percent for 2000-01) to a rate of 0.7 percent (from 2002-07) 13—implying a more gradual inflow of inexperienced persons into the workforce. Second, those newly employed in recent years should gain on-the-job experience and training.14

  • (iii) The third case assumes that a worker’s productive capacity depends on the type of job they fill. Two obvious distinctions are jobs in different sectors and regions of the economy—for example, an additional worker in the South may be less productive than in the North if the former has less capital/infrastructure available per worker (OECD, 2002). However, changes in the employment patterns across broad categories of regions and sectors do not appear significant since 1997: the share of employment in the Northern, Central and Southern regions has remained unchanged; while employment in the service sector has risen only slightly (from 61 to 63 percent) at the expense of agriculture and industry. Even so, there has been a sharp rise in the use of part-time and fixed-term labor contracts over the late 1990s (see Staff Report). It may be that many of these jobs are less productive, leading to a decline in measured TFP growth.15

  • A second factor contributing to the lower growth of measured TFP is the current slowdown in economic activity (which has occurred without a commensurate decline in employment growth). For the existing data, this is somewhat evident in 2001, but it is a more important consideration when extending the sample through the use of projections, given that GDP growth in 2002 is likely to be especially low (at less than 1 percent, see Staff Report). During slowdowns in economic activity, labor hoarding and low capacity utilization are likely to be prevalent especially given rigidities in the labor market arising from strong employment protection legislation in Italy (see Chapter HI of this report). These developments may not be adequately reflected in the measures of hours worked, or capacity utilization (also because these apply only to the industrial sector). Other things equal, this would lead to a temporary decline in measured TFP growth.

  • A third factor that should help to boost productivity going forward is the delayed impact of recent labor and product market reforms (for a discussion of these see Staff Report; a similar argument is made in the DPEF). Scarpetta and others (2002) find that industry productivity performance is negatively affected by strict product market regulations.16 On labor market regulation, they conclude that high hiring and firing costs seem to hinder productivity.

Table 2.

TFP Growth 1/

article image
Source: Decressin (2002), using OECD Economic Outlook data on the business sector (which excludes the public sector, though not public sector enterprises).

The qualitative results are not sensitive to the exact periods chosen. In particular, similar results are obtained if instead the second period, 1990-96, is either cut short or extended by one year (with a corresponding change to the third period), or if the third period, 1997-2001 is truncated at 2000.

23. A comparison of Italy with selected European economies also suggests that TFP growth in Italy will rebound from its very low level recorded in recent years. Tables 2 compares both actual and HP-filtered TFP growth across selected countries.17 After 1997, TFP growth declined in Germany and the Netherlands, and it was broadly stable for France and the United Kingdom (while it rose slightly for the United States). In all cases, however, actual and trend TFP growth (measured by the HP filtered series) remained considerably above that of Italy. It appears likely that TFP growth in Italy will converge to a rate that is at least close to that of these other economies, which enjoy similar institutional features and per capita incomes. This result is implied by empirical evidence from Bloom, Canning, and Sevilla (2002), based on a model of technological diffusion, and using a large cross-section of countries.18 While Italy already enjoys high levels of both labor and total factor productivity—comparable with other developed countries (see Hall and Jones, 1999; and Staff Report)—there is little reason to expect the growth rate of productivity to be substantially lower in Italy over an extended period.

24. In light of this discussion, it seems reasonable that trend TFP growth in Italy will recover to a rate comparable to that of these other selected European economies. This would also be consistent with TFP growth returning to the level seen in Italy in the first half of the 1990s. For this to occur, actual TFP growth will have to be slightly above that implied by the current WEO projections. This can be seen in Figure 2, which shows the estimates of actual TFP (as well as projections for 2002-07, as implied by current WEO projections for output, investment and employment growth). The rise in TFP from 2003 onwards arises from the expectation of economic recovery (with growth above the rate of potential output in order to close the current output gap). Figure 2 also shows the application of the HP filter to measured TFP—with the filter applied to data up to 2001, to 2004, and to 2007. Using these WEO projections implies that even with the anticipated rebound in actual TFP, trend TFP growth would be at most 0.8 percent per year,19 still somewhat below both the current rate for these other selected European countries, and Italy prior to 1997.

Figure 2.
Figure 2.

TFP Growth—Measured and Filtered, 1981-2007

(In percent)

Citation: IMF Staff Country Reports 2002, 232; 10.5089/9781451819830.002.A002

25. To achieve trend TFP growth in Italy of around 1.0 percent (by 2007), would imply annual actual TFP growth from 2002-07 of around 1.3 percent, somewhat above recent WEO projections. Figure 3 shows the required adjustment to actual TFP required for the period 2002-2007, and the HP filter applied to this series up to 2007. The chapter proceeds to calculate potential output on the basis of these new assumptions.

Figure 3.
Figure 3.

Adjusted TFP Growth, 1981-2007

(In percent)

Citation: IMF Staff Country Reports 2002, 232; 10.5089/9781451819830.002.A002

Production function results

26. Tables 3 presents the new production function estimates of the output gap, and potential growth, and compares them with the previous staff estimates. It also presents estimates based on a simple application of the HP filter to real GDP.

Table 3.

Output Gap and Potential Growth Estimates

article image

This rises to steadily to 2.0 percent in 2003. Half of this rise is due to a slowing in the assumed rate of population decline, the rest (in equal measure) by increases in the growth rates of trend participation and TFP.

Uses GDP estimates consistent with the adjusted TFP growth for 2002-07 described in paragraph 25.

27. Compared with the previous estimates, the new production function estimates imply a lower output gap (over recent years), and somewhat lower potential growth in 2001, but rising steadily to 2.1 percent by 2007. The revised output gap follows from lower-than-earlier-expected GDP growth from 1997 to 2001; this is reflected in relatively low TFP growth, especially given the higher-than-earlier-expected employment growth over this same period. Staff projections suggest future potential growth will recover to around 2.1 percent, in line with the anticipated gradual recovery in trend TFP growth, and continued employment growth (albeit at a more moderate pace than recent years). The sensitivity of these projections to employment growth is addressed when comparing these results with those of the Italian authorities in the following section.

28. Estimates based on a simple HP filter of real GDP imply a negligible output gap in the past two years, but similar potential growth in comparison with the production function results. Applying the HP filter to GDP (using the sample extended to 2007 to correct for the end-point problem) leads to a smaller output gap estimate than that of the production function approach. This difference primarily reflects the fact that the NAIRU estimate underlying the latter is somewhat below the unemployment rate from the mid to late 1990s, a period of gradual disinflation, and increased labor market flexibility (see Appendix II).

D. Comparison with EU, OECD and the Italian Authorities Estimates

29. This section provides a comparison of the production function estimates of the staff with those of the OECD, the EU Commission, and the Italian authorities. In terms of the current output gap, the new staff estimates are closer to the others, and the authorities than are the previous staff estimates, (Table 3 and 4). In contrast to the staff, OECD, and authorities, the new EU estimates imply that output was close to potential in 2000 and 2001.

Table 4.

Output Gap and Potential Growth, Production Function Estimates

article image
Sources: EU Commission; OECD; DPEF; and Fund staff estimates and projections.

Assumes that the output gap closes by 2007. Where potential growth estimates are not available to 2007, they are assumed to continue to grow at the same rate as in the last year provided.

Applies to 2004 only

The average for 1995 to 2003.

The average for 2004 to 2006, with a rising trend to 2.8 percent by 2006.

30. The EU, OECD, and the authorities have higher projections of future potential growth than staff. This is especially true for the OECD and the authorities, which project a sizable rise in potential growth around the middle of this decade. These differences generally reflect greater optimism regarding employment growth, and a stronger reversal of the decline in trend TFP growth.

31. Differences between staff estimates and those of these other institutions reflect a variety of factors:

  • EU Commission: The much lower output gap estimates follow largely from the relatively high NAIRU estimate of the EU 20—at 9.9 percent in 2001, it is above Italy’s current unemployment rate of 9.5 percent, and the staff estimate of the NAIRU of 8.8 percent in 2001. Staff estimates imply a more sizable decline in the NAIRU since the mid 1990s to a level that is below the current unemployment rate, as suggested by continuing wage moderation (Appendix II). The difference in the potential growth estimates is less marked. It partly follows from the fact that the EU assumes the same labor share of value, a, for all EU countries (equal to 0.63). Applying this to the staff model would raise potential output growth in Italy by about 0.1 percentage point per year—since the capital stock is projected to be growing faster the labor input. The EU also assume a slightly more rapid rebound in TFP growth from 2002 onwards.21

  • OECD: The larger output gap of the OECD appears to mostly reflect a higher estimate of trend TFP in 2001. This difference follows largely from the fact that the OECD apply the HP filter only over existing data. Doing this for the staff model would increase the estimated gap to -1.2 percent. The OECD estimate of the unemployment gap (that is, the ratio of actual unemployment to the NAIRU) is similar to that of the staff, especially for 2001 (see Appendix II). Hence, this is not a factor behind differences in the current output gap estimates. As for potential output growth, the main difference is based on the OECD projection of stronger employment growth. They project a steady rise in participation and a decline in the NAIRU, based on the impact of current reforms, together with the expectation of ongoing reform sufficient to achieve (at least to some extent), the Lisbon commitments on employment rates (OECD, 2002). Staff also anticipate a lagged impact of existing reforms on employment (mostly through participation), but base projections only on currently announced policies.

  • The Italian authorities: The authorities have a similar output gap in 2001, but the difference in potential output growth is sizable—reaching 0.7 percentage points by 2006. While the authorities (implicitly) project higher trend TFP growth (of about 0.1 percentage point annually), most of the difference in potential growth is accounted for by their assumption of higher employment growth—1.6 percent annually, compared with staff projections of average annual growth of 0.7 percent from 2002-07. Underlying this is a sizable fall in unemployment (to 6.8 percent in 2006, compared with a staff projection of 8.6 percent), and a large rise in the participation rate (to 65 percent in 2006, compared with a staff projection of 63.5 percent).22,23. The ambitiousness of these targets is illustrated in Figure 4, which shows the elasticity of employment with respect to real GDP. This rose sharply in the late 1990s, rebounding from earlier declines in unemployment. Staff projections imply that this elasticity will gradually return toward its historical average, while the authorities assume that it will stay well above this level. Achieving this would likely require additional and far-reaching labor market reforms. However, even if these were to be undertaken, the resulting employment growth may lead productivity growth to fall short of that underlying the authorities existing growth targets; in a similar fashion to the productivity slowdown from 1997 to 2001.24

Figure 4.
Figure 4.

Employment Elasticity with Respect to GDP, 1975-2007

(Over previous 5 years)

Citation: IMF Staff Country Reports 2002, 232; 10.5089/9781451819830.002.A002

32. The OECD and the authorities project much higher actual output growth than both the staff and the EU. The last column of Table 4 shows the annual average growth rates of output implied by the various institutions. These are calculated by assuming that the existing output gap is closed by 2007, and, therefore, provides a summary of the combined impact of the estimates of the output gap and projections of potential output growth. While the EU projects higher potential growth than the staff, the impact of this on output growth is partially offset by the smaller output gap estimated by the EU for 2001. In contrast, the difference between staff and the OECD regarding potential growth, combined with the larger output gap of the OECD for 2001, implies substantially higher output growth. The comparison between implied GDP growth rates of the staff and the authorities is made even more stark if GDP growth of only 0.6 percent is assumed for 2002 (as currently projected by staff and the authorities; see Staff Report). In this case, average annual growth for 2003-07 implied by staff projections is 2.5 percent, compared with 3.2 percent for the authorities.

E. Conclusion

33. New staff estimates suggest that the output gap in 2001 is lower than implied by previous estimates, but within the range of those of the EU Commission, the Italian authorities, and the OECD. This revised gap—of around -1 percent versus the previous estimate of-2 percent—largely reflects lower-than-earlier-expected output growth over the past few years. It falls within the range of the latest estimates from the EU Commission, the Italian authorities, and the OECD of-0.3, -0.8 and -1.4 percent, respectively. The much smaller gap estimate of the EU Commission reflects their higher NAIRU estimate, which is slightly above the current level of actual unemployment. In contrast, staff estimates imply a more sizable decline in the NAIRU over recent years—following from earlier labor market reforms—to a level still below the current unemployment rate, as suggested by continued moderate wage increases.

34. Though trend TFP growth has declined steadily over recent years, staff anticipate this to gradually recover, and for potential GDP growth to rise to slightly above its current level of 2.0 percent. The decline in Italian TFP growth since 1997 (as in the Netherlands) was more substantial than it was for the other large European economies, and it coincided with a surge in the growth rate of employment. Staff project employment growth to decline below the rapid pace of recent years, and for trend TFP growth to recover toward its pre-1997 level, in line with TFP growth of other European countries with similar institutional features and per capita incomes. This implies future potential output growth rising to 2.1 percent per year. The OECD and Italian authorities project much higher potential growth, driven mostly by projections of higher employment growth. Both recognize that continued employment growth of this magnitude will require further substantial labor market liberalization. Although, if this were to occur, it may work to dampen productivity growth by bringing less productive persons into the workforce.

APPENDIX I: Data

35. The following provides additional information regarding the data used, including the sources and nature of estimates and projections. Figure A1 shows a number of these series, including their HP filters where relevant.

  • a: labor share of income is calculated from ISTAT data by scaling upwards the share dependent employment income in value added (at market prices, excluding financial intermediation services indirectly measured, FISM), by the ratio of total employment to dependent employment.

  • Y, K, E: output, net capital stock, and employment data are from ISTAT, forecasts are based on current WEO projections.

  • util: survey measure of production capacity in use in industry, provided by the Bank of Italy. It is assumed to return to its sample average in 2002 and beyond, which at 92 percent is above the level of the first quarter 2002, but below the average of 2001 (around 93 percent). Potential utilization is based on the HP filter of this series.

  • WP: working age population data from the OECD, growth rates are as projected by ISTAT.

  • HW: hours worked in industry from ISTAT. For 2002 and beyond, it is assumed constant at the 2001 level. Potential hours worked is the HP filter of this series.

  • u and labor force: unemployment rate and labor force are from the ISTAT labor force survey. Forecasts are based on WEO projections.

  • pr: participation rate is the ratio of the labor force to WP. Under current WEO projections, this ratio grows steadily to 64 percent by 2007.

  • NAIRU: see Appendix II.

  • W: wages are the compensation rate of the business sector (annual salary per employee, in euros); data are from the OECD.

Figure A1.
Figure A1.

Italy: Actual Data, Projections, and HP Filtered Series, 1980-2007

Citation: IMF Staff Country Reports 2002, 232; 10.5089/9781451819830.002.A002

APPENDIX II: NAIRU Estimates

36. This appendix describes the construction of the NAIRU used in this paper, and compares it with OECD estimates.

37. The NAIRU is estimated using a simple method described by Giorno and others (1995).25 This starts by defining the NAIRU as the level of unemployment above (below) which inflation is falling (rising): 26

D2logW=-a(U-NAIRU),α>0(A1)

where: W is the nominal wage level, U is the actual unemployment level, and D is the first difference operator. An estimate of α can be obtained by applying the approximation that the NAIRU is constant between any two consecutive periods, in which case:

â=-D3logw/DU(A2)

Combining equations (Al) and (A2) provides an estimate of the NAIRU:

NAIRU=U-D2logW/â(A3)

38. The resulting series is smoothed to eliminate erratic components.27 Figure A2 compares actual employment with this (initial) estimate of the NAIRU (labeled NAIRU1). Further smoothing is conducted to produce the final estimate of the NAIRU (labeled NAIRU2)—these modifications reflect the view that the true NAIRU is not likely to have declined in the early 1990s (as implied by NAIRU), and that labor market reforms are likely to have led to a decline in the NAIRU in the mid 1990s (somewhat earlier than suggested by NAIRU1).

Figure A2.
Figure A2.

Unemployment Rate and the NAIRU,1980-2001

(In Percent)

Citation: IMF Staff Country Reports 2002, 232; 10.5089/9781451819830.002.A002

39. Four comments regarding the NAIRU estimate are warranted:

  • First, the new estimates imply an unemployment gap (the difference between unemployment and the NAIRU) that is relatively close to that produced by the OECD, especially in 2001 (Figure A3).

  • Second, the unemployment gap from 1980 to 2001 is estimated to have been positive on average, due largely to observations after 1994 (the average gap until that time was only 0.1 percentage point). The gap was especially large from 1997 to 1999. While this was a period when reforms were leading to greater labor market flexibility, it was also a time of sizable adverse shocks to labor demand—following from tighter monetary policy and sizable fiscal consolidation necessary to help meet the Maastricht criteria. Hence, it was possible for unemployment to remain high, and even rise, at a time when the NAIRU was thought to be on the decline.

  • Third, these estimates are comparable to those implied by the bivariate model of the NAIRU presented by Boone and others (2002). Their model produces a range of estimates depending on the specification of the volatility of the NAIRU relative to the unemployment gap. Using a range of values for this volatility parameter that they argue is “reasonable” produces a range of NAIRU estimates spanning those presented above; these estimates also imply a persistent unemployment gap over the past decade or more.

  • Fourth, staff project that on current policies, the NAIRU will decline only in the coming years, from 8.8 percent in 2001, to 8.7 percent in 2002, and 8.6 percent thereafter.

Figure A3.
Figure A3.

Unemployment Gap Estimates

(In Percentage points)

Citation: IMF Staff Country Reports 2002, 232; 10.5089/9781451819830.002.A002

  • Ahn, S., 2002, “Competition, Innovation and Productivity Growth: A Review of Theory and Evidence,OECD Economics Department Working Paper, no. 317.

    • Search Google Scholar
    • Export Citation
  • Barro, R. and X. Sala-i-Martin, 1995, Economic Growth (New York: McGraw-Hill).

  • Baxter, M. and R.G King, 1995, “Measuring Business Cycles: Approximate Band-Pass Filters for Economic Time Series,NBER Working Paper no. 5022(Cambridge, Massachusetts: National Bureau of Economic Research).

    • Search Google Scholar
    • Export Citation
  • Bentolila, S. and G. Saint-Paul, 1998, “Explaining Movements in the Labour Share,CEPR Discussion Paper no. 1958 (London: Centre for Economic Policy Research).

    • Search Google Scholar
    • Export Citation
  • Bloom, D.E., D. Canning, and J. Sevilla, 2002, “Technological Diffusion, Conditional Convergence, and Economic Growth,NBER Working Paper no. 8713 (Cambridge, Massachusetts: National Bureau of Economic Research).

    • Search Google Scholar
    • Export Citation
  • Boone, L., M. Juillard, D. Laxton, and P. N’Diaye, 2002, “How Well Do Alternative Time-Varying Parameter Models of the NAIRU Help Policymakers Forecast Unemployment and Inflation in the OECD Countries,IMF Working Paper, forthcoming.

    • Search Google Scholar
    • Export Citation
  • Brandolini, A. and P. Cipollone, 2001, “Multifactor Productivity and Labour Quality in Italy, 1981-2000,Bank of Italy, Economic Research Discussion Paper no. 422.

    • Search Google Scholar
    • Export Citation
  • De Masi, P. R., 1997, “IMF Estimates of Potential Output: Theory and Practice,IMF Working Paper 97/177(Washington: International Monetary Fund).

    • Search Google Scholar
    • Export Citation
  • Decressin, J., 2002, “Growth and Adjustment in Germany; Perspectives and Prospects,forthcoming IMF Selected Issues Paper.

  • Decressin, J., and others, 2001, Selected Euro-Area Countries: Rules-Based Fiscal Policy and Job-Rich Growth in France, Germany, Italy, and Spain, IMF country Report. No.01/203(Washington: International Monetary Fund).

    • Search Google Scholar
    • Export Citation
  • Elmeskov, J., 1993, “High and Persistent Unemployment: Assessment of the Problem and Its Causes,OECD Economics Department Working Paper No.132.

    • Search Google Scholar
    • Export Citation
  • European Commission, 1999, “Comparison of Trend Estimation Methods,issues paper for the EPC Working Group on output gaps, II/346/99/EN.

    • Search Google Scholar
    • Export Citation
  • Giorno, C., P. Richardson, D. Roseveare, and P. van den Noord, 1995, “Estimating Potential Output, Output Gaps and Structural Budget Balances,OECD Economic Studies, 24, pp. 167209.

    • Search Google Scholar
    • Export Citation
  • Hall, R.E. and C.I. Jones 1999, “Why do Some Countries Produce So Much More Output Per Worker than Others?The Quarterly Journal of Economics, 114:83116.

    • Search Google Scholar
    • Export Citation
  • Mc Morrow, K. and W. Roeger, 2001, “Potential Output: Measurement Methods, ‘New’ Economy Influences and Scenarios for 2001-10—A Comparison of the EU15 and the U.S.,European Commission Economic Papers No.150.

    • Search Google Scholar
    • Export Citation
  • OECD, 2002, OECD Economic Surveys, 2001-02, Italy.

  • Scarpetta, S., P. Hemmings, T. Tressel, and J. Woo, 2002, “The Role of Policy and Institutions for Productivity and Firm Dynamics: Evidence from Micro and Industry data,OECD Economics Department Working Papers No.329.

    • Search Google Scholar
    • Export Citation
  • Willman, A., 2002, “Euro Area Production Function and Potential Output: A Supply Side System Approach,ECB Working Paper Series No.153.

    • Search Google Scholar
    • Export Citation
1

Prepared by Christopher Kent.

2

But rising to 2.0 percent in 2000.

3

De Masi (1997) provides a survey regarding the application of this approach within the IMF. Mc Morrow and Roeger (2001) describe the production function approach and compare it with other approaches to estimating potential output.

4

Willman (2002) examines the more general constant elasticity of substitution (CES) production function. He presents evidence based on the euro area that suggests the Cobb-Douglas function provides a good approximation and, moreover, that output gap estimates are relatively insensitive to alternative parameterizations and functional forms of the underlying production function.

5

The labor share does vary over time—rising from 0.71 in 1970 to 0.77 in 1975 and then declining steadily to 0.62 by 2001. Estimates of the gap and potential output growth presented below are, however, broadly unchanged if instead the labor share is assumed equal to the level of 2001, Giving greater weight to the capital input in this way reduces the output gap in 2001 by only 0.06 percentage points, and increases potential growth by 0.1 percentage points (by 2007) relative to results presented in Tables 3 and 4. For a discussion of the determinants of the labor share and its evolution in the OECD see Bentolila and Saint-Paul (1998).

6

Another possibility is to acknowledge differences in the quality/skill of different labor inputs (as done, for example, in Brandolini and Cipollone, 2001, discussed below).

7

In short, this was done by regressing TFP measured as per equation (1) on util, a constant, and a time trend, and then testing whether the coefficient on util was significantly different from a=0.7.

8

Of course the same problem applies also to the beginning of the sample, but for policy purposes the focus is on the current output gap and future potential output

9

This is the standard approach used by the IMF and the OECD when applying the production function methodology (European Commission 1999).

10

Baxter and King (1995) show that the HP filter tends to give a disproportionate emphasis to the end-points of the cycle (the first and last 3-4 observations), if no corrective measures are applied. Mc Morrow and Roeger (2001) also find this when estimating potential output for EU countries by applying an HP filter to real GDP. They find that a forecasting error of plus or minus 0.5 percentage points alters the estimate of the output gap by around 0.2 percentage points. Moreover, this sensitivity is similar across EU countries and does not appear to be strongly related to the cyclical position.

11

It is worth distinguishing the two roles played by these projections. The first is to help mitigate the impact of the end-point problem on estimates of the output gap up to 2001. The second is to provide inputs to form a projection for future potential output growth.

12

The growth of employment over the late 1990s occurred despite weaker growth in labor productivity in part because of wage moderation (Decressin and others, 2001). Also, labor market reforms allowed for more flexible use of labor—including the use of atypical contracts (see Staff Report)—supporting greater employment of women, and of youth.

13

This argument is similar to one made in the authorities new medium-term program (Documento di Programmazione Economico-Finanziaria, DPEF, July 2002), although the authorities assume annual employment growth to slow to only 1.6 percent. Though partly cyclical in nature, there is already evidence of slower employment growth in 2002.

14

Indeed, to the extent that on-the-job experience/training is facilitated by the initial level of education, the trend rise in schooling will help to reinforce this process.

15

Cases (ii) and (iii) may be closely related, since the relaxation of constraints on these forms of employment is likely to have facilitated the entry of otherwise less experienced/productive persons into the workforce.

16

Ahn (2001) provides a comprehensive review of the empirical literature in this area and confirms that the link between product market competition and productivity growth is positive and significant.

17

Calculations are from Decressin (2002)—kindly provided by the author—based on OECD business sector data. Table 1 and 2 data are not exactly comparable, since the former are based on economy—wide measures of growth. Nevertheless, at least for Italy the difference in measured TFP growth is not significant.

18

Laxton (1999) also finds evidence of catch-up of levels of labor productivity in Italy to that of the United States over the longer term. These findings of TFP convergence are similar in spirit to the finding of “conditional convergence" (see for example, Barro and Sala-i-Martin, 1995) based on catch-up of the capital stock to steady state levels.

19

Trend TFP growth as implied by applying the HP filter up to 2004 (that is, the correction for the end-point problem suggested by Baxter and King, 1995) is only 0.5 percent per year, while extending the filter to 2007 implies trend TFP growth in 2001 of only 0.7 percent. Both of these are lower than obtained by ignoring the end-point problem—that is, applying the HP filter up to only 2001.

20

To estimate the NAIRU, the EU adopt a combined Kalman filter and Phillips curve approach, whereby the deviation of unemployment from the NAIRU is negatively related to the change in wage inflation, controlling for other temporary shocks to wage inflation. One feature of their approach is that the unemployment gap is restricted to have a mean of zero over the sample period (so as to also ensure a symmetrical output gap over the sample).

21

As in this chapter, the EU estimate trend TFP growth by using the HP filter and extending the sample period beyond 2001 using projections.

22

The DPEF does not specify participation rates. These are calculated by assuming that the projections forworking age population are the same as those used by the staff (see Appendix 1). Just over half of the difference in projected employment growth rates is accounted for by the lower unemployment rate projected by the authorities, the remainder by their higher participation rate projection.

23

Using the authorities projections for participation within the staff model would imply an increase in the estimated 2001 output gap of around 0.4 percentage points. This arises from the fact that assuming a higher future participation rate reduces the gap between the current actual and trend participation rates to near zero (the staff estimate this gap to be 0.5 percentage points in 2001).

24

The OECD (2002) argue that rapid employment growth (toward the Lisbon target levels) would suppress productivity growth because it implies bringing into the workforce a large number of persons not previously employed (especially from the South), for whom the productivity level is on average lower than that of the existing workforce.

25

This method was originally espoused by Elmeskov (1993) who showed that the estimates were similar to those from comparable methods based on the alternative Okun’s law or Beveridge curve relationships.

26

Wage inflation is used, since the link to unemployment gap is more direct than it is for inflation of goods and services.

27

This is done by first replacing outlying observations—arising in a few periods when wage inflation is almost constant between two years—with linear interpolations, and then applying a moving average filter to the series. Also, the sample period is extended to 2003 using forecasts to help avoid the end-point problem.

Italy: Selected Issues
Author: International Monetary Fund