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Effects of productivity shocks on hours worked: UK evidence

  • Hashmat Khan und John Tsoukalas EMAIL logo
Veröffentlicht/Copyright: 26. September 2013
The B.E. Journal of Macroeconomics
Aus der Zeitschrift The B.E. Journal of Macroeconomics Band 13 Heft 1

Abstract

We provide evidence that positive industry-level productivity shocks cause hours worked to fall in the short run in the UK economy. We use UK industry data, which covers both manufacturing and non-manufacturing industries, and identify productivity shocks using long-run restrictions and structural vector autoregression methodology. Our findings show that the unconditional correlation between growth rates of productivity and hours is negative in almost all the industries, and the correlation conditional on productivity shocks is negative in over three-quarters of the industries. After a positive productivity shock, hours fall in 26 of the 31 industries. The findings at the aggregate level are consistent with those at industry level. We note some striking differences in comparison to the recent US literature. Significantly larger capital adjustment costs in the UK help account for the UK-US differences. Moreover, UK industries with higher investment elasticities (lower capital adjustment costs) have less negative impact effects of hours.

Keywords: business cycles; hours; productivity shocks; JEL Classification: E32; E24
Corresponding author: John Tsoukalas, Business School, Department of Economics, Adam Smith Building, University of Glasgow, Glasgow, G12 8RT, UK, e-mail:
  1. 1

    Earlier work of Kiley (1998) used industry-level labor productivity and found that employment falls in the US manufacturing industries after a positive productivity shock. Chang and Hong (2006), however, point out that TFP is a superior measure of productivity than labor productivity as the latter is confounded by changes in input mix. Shea (1998) used R&D data and found that employment rises in the short run but falls in the long-run after a positive productivity shock.

  2. 2

    Even though productivity may be affected by non-technology related shocks [such as the uncertainty shocks identified in Bloom (2009) and Alexopoulos and Cohen (2009b)], in this paper, we use the terminology “productivity shocks” and “technology shocks” interchangeably.

  3. 3

    Khan and Tsoukalas (2006) provide a detailed analysis of the sources of UK business cycles at the aggregate level using the SVAR methodology.

  4. 4

    The UK evidence at the aggregate level is consistent with the US evidence previously presented in Galí (1999), Francis and Ramey (2005), and more recently, some evidence in Alexopoulos and Tombe (2012) on the possible short run negative response of hours to innovations in management techniques.

  5. 5

    Wang and Wen (2011) present a real multi-sector model of entry and exit of firms with the time-to-build feature in which both employment and investment fall, and output rises on impact after a positive technology shocks. They argue that this model can match the empirical evidence in Basu et al. (2006) without necessarily invoking the price stickiness assumption.

  6. 6

    See, for example, Shapiro and Watson (1988), Blanchard and Quah (1989), and King et al. (1991) for early contributions to the SVAR literature.

  7. 7

    Note that we use z to indicate that the correlations are conditional on the productivity shock

  8. 8

    In many industries the estimated negative covariance between TFP growth and hours growth, conditional on the productivity shock, is about the same magnitude as the respective conditional variances in the two series, leading to highly negative conditional correlations. Previously, a similar high negative conditional correlation in the UK aggregate data was reported in Galí (1999) who found that the conditional correlation between labor productivity growth and employment growth from 1962:1–1994:3 was –0.91.

  9. 9

    We thank Ellen McGrattan for kindly providing us with this data.

  10. 10

    Basu et al. (2006) provide correlations between TFP growth and hours growth are at the sector (one-digit) level. The UK analysis we conduct is at the two-digit level.

  11. 11

    In terms of correlations, for example, both unconditional and conditional correlations between labor productivity growth and hours growth for the oil and gas industry are negative and statistically significant for the labor productivity case. Thus, this particular case highlights the point in Chang and Hong (2006) that shocks that have a long run effect on input mix growth could also lower hours even when TFP shocks raise hours on impact (as shown in Table 2). Table A5 in the Appendix provides industry-by-industry labor productivity based results.

  12. 12

    See Table A6, Appendix.

  13. 13

    Khan and Tsoukalas (2006) report aggregate results for the UK based on quarterly data and labor productivity (output per worker hour) for the period 1964–2004. Francis (2009) reports findings using aggregate annual historical UK data.

  14. 14

    Table 4 in Groth (2008).

  15. 15

    Since the BEID data is from 1970 to 2000, there is no overlap with the micro data used in Bunn and Ellis (2012b). Greenslade and Parker (2008) conducted an analysis of survey data from 693 UK companies to determine how often they change prices. Approximately 45% of the firms in the sample change price between 6 months to a year, with about 35% changing prices annually. Moreover, approximately 55% of the companies in the manufacturing sector change prices between 6 months to a year, and the same goes for about 60% of the companies in the hotels and restaurants sector.

  16. 16
  17. 17

    We do not conduct the SVAR analysis as it is constrained by the short sub-sample periods.

  18. 18

    The annual NES data is from 1969 to 1999.

  19. 19

    Industry by industry results are presented in Table A1.

  20. 20

    Table A3 in Appendix.

  21. 21

    Table A4 in the Appendix.

  22. 22

    The findings for the 5% markup case are similar and not reported here.

We thank John Fernald for helpful discussions at an early stage of this project. We also thank two anonymous referees and participants at the Canadian Economic Association Meetings (Ottawa, 2011) for helpful comments and suggestions.

Appendix of Robustness Tables

Table A1

Total factor productivity (utilization corrected) and hours worked.

IndustryCorr(ΔTFP, Δh)Corr(ΔTFP, Δh∣z)Impact effect on hours
1. Agriculture–0.13 [0.43]0.50 [0.59]+
2. Oil and gas0.23 [0.30]0.70 [0.62]+
3. Coal and other mining–0.30 [0.02]–0.64 [0.00]–**
4. Manufacturing fuel (ND, mfg)–0.66 [0.07]–0.99 [0.00]–**
5. Chemicals and pharmaceuticals (ND, mfg)–0.18 [0.18]–0.83 [0.00]–**
6. Non-metallic mineral products (D, mfg)–0.07 [0.68]–0.82 [0.21]–
7. Basic metals and metal goods (D, mfg)–0.16 [0.40]–0.87 [0.00]–**
8. Mechanical engineering (D, mfg)–0.05 [0.69]–0.85 [0.00]–**
9. Electrical engineering and electronics (D, mfg)0.13 [0.24]0.98 [0.03]+
10. Vehicles (D, mfg)–0.35 [0.12]–0.99 [0.05]–**
11. Food, drink, and tobacco (ND, mfg)–0.60 [0.03]–0.85 [0.00]–**
12. Textiles, clothing and leather (ND, mfg)–0.02 [0.81]–0.35 [0.30]–
13. Paper, printing and publishing (ND, mfg)–0.06 [0.63]–0.56 [0.07]–
14. Other manufacturing (D, mfg)0.24 [0.16]0.06 [0.89]0
15. Electric supply–0.11 [0.66]0.05 [0.73]–
16. Gas supply–0.66 [0.07]–0.99 [0.06]–**
17. Water supply–0.05 [0.27]0.15 [0.82]+
18. Construction–0.09 [0.55]–0.76 [0.09]0
19. Wholesale, vehicle sales and repairs–0.32 [0.21]0.37 [0.57]0
20. Retailing–0.53 [0.00]–0.58 [0.46]–
21. Hotels and catering–0.42 [0.00]–0.98 [0.04]–**
22. Rail transport–0.87 [0.16]–0.99 [0.00]–**
23. Road transport–0.69 [0.00]–0.99 [0.00]–**
24. Water transport–0.49 [0.06]–0.99 [0.07]–**
25. Air transport–0.29 [0.06]–0.97 [0.22]–
26. Other transport services–0.32 [0.05]–0.90 [0.11]–
27. Communications–0.27 [0.21]–0.99 [0.00]–**
28. Finance–0.47 [0.03]–0.99 [0.00]–**
29. Business services–0.36 [0.04]–0.96 [0.00]–
33. Waste treatment–0.04 [0.85]0.41 [0.54]+
34. Miscellaneous services–0.79 [0.03]–0.84 [0.00]–**

The industry results are based on a bi-variate SVAR: [ΔTFPi,corr Δh]′, where ΔTFPi,corr is the utilization corrected TFP growth. p-Values in square brackets. ** denotes statistical significance at 5% level. Public sector industries in the BEID (numbered 30, 31, 32) are excluded.

Table A2

Total factor productivity and hours worked: controlling for aggregate TFP.

IndustryCorr(ΔTFP, Δh)Corr(ΔTFP, Δh∣z)Impact effect on hours
1. Agriculture–0.11 [0.54]0.39 [0.08]+
2. Oil and gas0.24 [0.19]0.88 [0.07]+
3. Coal and other mining–0.29 [0.10]–0.94 [0.00]–**
4. Manufacturing fuel (ND, mfg)–0.64 [0.00]–0.99 [0.00]–**
5. Chemicals and pharmaceuticals (ND, mfg)–0.20 [0.26]–0.94 [0.00]–**
6. Non-metallic mineral products (D, mfg)–0.09 [0.62]–0.98 [0.00]–**
7. Basic metals and metal goods (D, mfg)–0.16 [0.38]–0.91 [0.00]–**
8. Mechanical engineering (D, mfg)–0.05 [0.79]–0.94 [0.00]–**
9. Electrical engineering and electronics (D, mfg)0.13 [0.40]0.33 [0.07]+
10. Vehicles (D, mfg)–0.36 [0.04]–0.99 [0.00]–**
11. Food, drink, and tobacco (ND, mfg)–0.59 [0.00]–0.94 [0.00]–**
12. Textiles, clothing and leather (ND, mfg)–0.12 [0.41]–0.73 [0.00]–**
13. Paper, printing and publishing (ND, mfg)–0.05 [0.76]0.20 [0.29]–
14. Other manufacturing (D, mfg)0.25 [0.18]0.76 [0.00]0
15. Electric supply–0.12 [0.51]0.06 [0.71]–
16. Gas supply–0.64 [0.00]–0.99 [0.00]–**
17. Water supply–0.28 [0.12]0.51[0.00]0
18. Construction–0.08 [0.66]0.84 [0.00]–
19. Wholesale, vehicle sales and repairs–0.31 [0.09]0.97 [0.00]+
20. Retailing–0.50 [0.00]–0.99 [0.00]–
21. Hotels and catering–0.39 [0.03]–0.35 [0.06]–
22. Rail transport–0.86 [0.00]–0.99 [0.00]–**
23. Road transport–0.68 [0.00]–0.99 [0.00]–**
24. Water transport–0.47 [0.00]–0.99 [0.00]–**
25. Air transport–0.29 [0.11]–0.82 [0.00]–
26. Other transport services–0.30 [0.10]–0.95 [0.00]–
27. Communications–0.23 [0.21]0.56 [0.00]–
28. Finance–0.54 [0.00]–0.98 [0.00]–**
29. Business services–0.36 [0.04]–0.96 [0.00]–
33. Waste treatment–0.17 [0.36]–0.53 [0.00]–
34. Miscellaneous services–0.78 [0.00]–0.41 [0.02]–**

The industry results are based on a tri-variate SVAR: [ΔTFPa ΔTFPi Δh]’. p-Values in square brackets. ** denotes statistical significance at 5% level. Public sector industries in the BEID (numbered 30, 31, 32) are excluded.

Table A3

Total factor productivity and hours worked: larger SVAR.

IndustryCorr(ΔTFP, Δh∣z)Impact effect on hours
1. Agriculture–0.85 [0.00]–
2. Oil and gas0.96 [0.00]+
3. Coal and other mining–0.95 [0.00]–**
4. Manufacturing fuel (ND, mfg)–0.98 [0.00]–**
5. Chemicals and pharmaceuticals (ND, mfg)–0.86 [0.00]–**
6. Non-metallic mineral products (D, mfg)–0.41 [0.02]–
7. Basic metals and metal goods (D, mfg)–0.89 [0.00]–**
8. Mechanical engineering (D, mfg)–0.97 [0.00]–**
9. Electrical engineering and electronics (D, mfg)0.79 [0.00]+
10. Vehicles (D, mfg)–0.98 [0.00]–
11. Food, drink, and tobacco (ND, mfg)–0.99 [0.00]–**
12. Textiles, clothing and leather (ND, mfg)–0.31 [0.09]–**
13. Paper, printing and publishing (ND, mfg)0.09 [0.63]–
14. Other manufacturing (D, mfg)0.44 [0.01]–
15. Electric supply–0.35 [0.05]–**
16. Gas supply–0.99 [0.00]–**
17. Water supply–0.90 [0.00]–**
18. Construction0.88 [0.00]+
19. Wholesale, vehicle sales and repairs0.97 [0.00]+
20. Retailing–0.09 [0.61]–
21. Hotels and catering–0.98 [0.00]–**
22. Rail transport–0.98 [0.00]–
23. Road transport–0.99 [0.00]–**
24. Water transport–0.96 [0.00]–
25. Air transport–0.51 [0.00]–**
26. Other transport services–0.97 [0.00]–
27. Communications0.77 [0.00]+
28. Finance–0.99 [0.00]–
29. Business services–0.99 [0.00]–
33. Waste treatment–0.66 [0.00]–
34. Miscellaneous services–0.50 [0.00]–

The industry results are based on a SVAR specification (4.3). ND, non-durable; D, durable; mfg, manufacturing; SIC92, UK’s Standard Industrial Classification (1992). The p-values are in square brackets. ** indicates significant at 5% level.

Table A4

Total factor productivity (markup corrected) and hours worked (quadratic detrended).

IndustryCorr(ΔTFP, hQD)Corr(ΔTFP, hQD∣z)Impact effects
QD hoursTFP (μ=0.1)
1. Agriculture–0.04 [0.39]–0.33 [0.30]–+
2. Oil and gas–0.06 [0.28]–0.94 [0.73]–+
3. Coal and other mining–0.10 [0.55]–0.14 [0.45]––**
4. Manufacturing fuel (ND, mfg)–0.03 [0.38]0.86 [0.38]+–**
5. Chemicals and pharmaceuticals (ND, mfg)–0.50 [0.00]–0.98 [0.00]–**–**
6. Non-metallic mineral products (D, mfg)–0.29[0.08]–0.99 [0.00]–**–**
7. Basic metals and metal goods (D, mfg)–0.51 [0.19]–0.98 [0.00]–**–**
8. Mechanical engineering (D, mfg)–0.48 [0.03]–0.99 [0.00]–**–**
9. Electrical engineering and electronics (D, mfg)0.43 [0.41]0.85 [0.00]+**+
10. Vehicles (D, mfg)–0.39[0.28]–0.74 [0.02]–**–**
11. Food, drink, and tobacco (ND, mfg)–0.57 [0.09]–0.89 [0.51]––**
12. Textiles, clothing and leather (ND, mfg)–0.26 [0.63]–0.96 [0.00]–**–**
13. Paper, printing and publishing (ND, mfg)–0.07[0.78]–0.44 [0.82]––
14. Other manufacturing (D, mfg)–0.13 [0.55]–0.98 [0.00]–**0
15. Electric supply–0.01 [0.33]0.31 [0.46]0–
16. Gas supply–0.02 [0.45]0.32 [0.76]+–
17. Water supply–0.41 [0.19]0.30 [0.37]+0
18. Construction–0.28 [0.38]–0.89 [0.08]––
19. Wholesale, vehicle sales and repairs0.23 [0.20]0.35 [0.23]++
20. Retailing–0.34 [0.00]–0.77 [0.00]–**–
21. Hotels and catering–0.35 [0.41]–0.70 [0.92]––
22. Rail transport–0.42 [0.77]–0.50 [0.25]––**
23. Road transport–0.57 [0.00]–0.76 [0.00]–**–**
24. Water transport–0.24 [0.54]–0.10 [0.49]0–**
25. Air transport–0.34 [0.03]–0.75 [0.87]––
26. Other transport services–0.29 [0.46]–0.95 [0.08]––
27. Communications–0.32 [0.67]–0.07 [0.03]––
28. Finance–0.55 [0.02]–0.72 [0.02]–**–**
29. Business services–0.50 [0.04]–0.72 [0.09]––
33. Waste treatment–0.41 [0.35]–0.61 [0.18]––
34. Miscellaneous services–0.32 [0.02]–0.81 [0.26]–**–**

The industry results are based on a tri–variate SVAR: [ΔTFPa ΔTFPihQD]’. ND, non-durable; D, durable; mfg, manufacturing; SIC92, UK’s Standard Industrial Classification (1992). The p-values are in square brackets. ** indicates significant at 5% level.

Table A5

Labor productivity (LP) growth and hours worked.

IndustryCorr(ΔLP, Δh)Corr(ΔLP, Δh∣z)Impact effect on hours
1. Agriculture–0.89 [0.00]–0.99 [0.00]–**
2. Oil and gas–0.71 [0.08]–0.86 [0.01]–**
3. Coal and other mining–0.61 [0.04]–0.90 [0.00]–**
4. Manufacturing fuel (ND, mfg)–0.57 [0.10]–0.99 [0.01]–**
5. Chemicals and pharmaceuticals (ND, mfg)–0.30 [0.17]–0.42 [0.54]–
6. Non-metallic mineral products (D, mfg)–0.53 [0.02]–0.97 [0.15]–**
7. Basic metals and metal goods (D, mfg)–0.12 [0.48]–0.16 [0.83]–
8. Mechanical engineering (D, mfg)–0.23 [0.15]–0.99 [0.04]–**
9. Electrical engineering and electronics (D, mfg)–0.18 [0.24]0.88 [0.56]+
10. Vehicles (D, mfg)0.28 [0.09]–0.92 [0.58]–
11. Food, drink, and tobacco (ND, mfg)–0.80 [0.00]–0.99 [0.13]–**
12. Textiles, clothing and leather (ND, mfg)–0.28 [0.05]0.02 [0.99]+
13. Paper, printing and publishing (ND, mfg)–0.02 [0.16]–0.76 [0.00]–**
14. Other manufacturing (D, mfg)0.01 [0.96]–0.26 [0.84]–
15. Electric supply–0.60 [0.04]–0.99 [0.01]–**
16. Gas supply–0.81 [0.08]–0.99 [0.15]–**
17. Water supply–0.87 [0.11]–0.99 [0.09]–**
18. Construction–0.40 [0.05]–0.98 [0.00]–**
19. Wholesale, vehicle sales and repairs–0.48 [0.14]–0.90 [0.44]–
20. Retailing–0.58 [0.07]–0.79 [0.01]–
21. Hotels and catering–0.31 [0.00]–0.04 [0.98]–
22. Rail transport–0.89 [0.14]–0.99 [0.00]–**
23. Road transport–0.74 [0.00]–0.99 [0.00]–**
24. Water transport–0.68 [0.11]–0.99 [0.19]–
25. Air transport–0.57 [0.00]–0.97 [0.00]–**
26. Other transport services–0.31 [0.12]0.51 [0.39]0
27. Communications–0.09 [0.36]–0.47 [0.36]0
28. Finance–0.64 [0.00]–0.99 [0.00]–**
29. Business services–0.48 [0.00]–0.99 [0.04]–**
33. Waste treatment–0.73 [0.00]–0.99 [0.00]–**
34. Miscellaneous services–0.88 [0.06]–0.99 [0.14]–**

The industry results are based on a bi-variate SVAR: [ΔLPi Δh]′, where ΔLPi is the labor productivity growth. p-Values in square brackets. **denotes statistical significance at 5% level. Public sector industries in the BEID (numbered 30, 31, 32) are excluded.

Table A6

Permanent input-mix shocks and hours worked.

IndustryMaterial-labor shockCapital-labor shock
1. Agriculture–**–
2. Oil and gas–**–**
3. Coal and other mining–**–
4. Manufacturing fuel (ND, mfg)–**–
5. Chemicals and pharmaceuticals (ND, mfg)+–
6. Non-metallic mineral products (D, mfg)––**
7. Basic metals and metal goods (D, mfg)–**–
8. Mechanical engineering (D, mfg)––
9. Electrical engineering and electronics (D, mfg)––**
10. Vehicles (D, mfg)––**
11. Food, drink, and tobacco (ND, mfg)–**–
12. Textiles, clothing and leather (ND, mfg)+–
13. Paper, printing and publishing (ND, mfg)––
14. Other manufacturing (D, mfg)––**
15. Electric supply–**–
16. Gas supply–**–**
17. Water supply–**–
18. Construction–**–**
19. Wholesale, vehicle sales and repairs–**–
20. Retailing–**+
21. Hotels and catering+–
22. Rail transport–**–**
23. Road transport–**–**
24. Water transport+–**
25. Air transport–**–**
26. Other transport services+–
27. Communications–+
28. Finance–**+
29. Business services–**+
33. Waste treatment–**–**
34. Miscellaneous services–**–**

The industry results are based on a bi-variate SVARs [Δ(m–l)t Δh]′ (column 2) where Δ(m–l)t is material-labor ratio growth and [Δ(k–l)t Δh]′ (column 3) where Δ(k–l)t is capital-labor ratio growth. **denotes statistical significance at 5% level. Public sector industries in the BEID (numbered 30, 31, 32) are excluded.

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Received: 2012-9-27
Accepted: 2013-8-9
Published Online: 2013-09-26
Published in Print: 2013-01-01

©2013 by Walter de Gruyter Berlin Boston

Artikel in diesem Heft

  1. Masthead
  2. Masthead
  3. Advances
  4. How have global shocks impacted the real effective exchange rates of individual euro area countries since the euro’s creation?
  5. Employment by age, education, and economic growth: effects of fiscal policy composition in general equilibrium
  6. Overeducation and skill-biased technical change
  7. Strategic wage bargaining, labor market volatility, and persistence
  8. Households’ uncertainty about Medicare policy
  9. Contributions
  10. Deconstructing shocks and persistence in OECD real exchange rates1)
  11. A contribution to the empirics of welfare growth
  12. Development accounting with wedges: the experience of six European countries
  13. Implementation cycles, growth and the labor market
  14. International technology adoption, R&D, and productivity growth
  15. Bequest taxes, donations, and house prices
  16. Business cycle accounting of the BRIC economies
  17. Privately optimal severance pay
  18. Small business loan guarantees as insurance against aggregate risks
  19. Output growth and unexpected government expenditures
  20. International business cycles and remittance flows
  21. Effects of productivity shocks on hours worked: UK evidence
  22. A prior predictive analysis of the effects of Loss Aversion/Narrow Framing in a macroeconomic model for asset pricing
  23. Exchange rate pass-through and fiscal multipliers
  24. Credit demand, credit supply, and economic activity
  25. Distortions, structural transformation and the Europe-US income gap
  26. Monetary policy shocks and real commodity prices
  27. Topics
  28. News-driven international business cycles
  29. Business cycle dynamics across the US states
  30. Required reserves as a credit policy tool
  31. The macroeconomic effects of the 35-h workweek regulation in France
  32. Productivity and resource misallocation in Latin America1)
  33. Information and communication technologies over the business cycle
  34. In search of lost time: the neoclassical synthesis
  35. Divorce laws and divorce rate in the US
  36. Is the “Great Recession” really so different from the past?
  37. Monetary business cycle accounting for Sweden
https://doi.org/10.1515/bejm-2012-0056
Schlagwörter für diesen Artikel
business cycles; hours; productivity shocks; JEL Classification: E32; E24

Artikel in diesem Heft

  1. Masthead
  2. Masthead
  3. Advances
  4. How have global shocks impacted the real effective exchange rates of individual euro area countries since the euro’s creation?
  5. Employment by age, education, and economic growth: effects of fiscal policy composition in general equilibrium
  6. Overeducation and skill-biased technical change
  7. Strategic wage bargaining, labor market volatility, and persistence
  8. Households’ uncertainty about Medicare policy
  9. Contributions
  10. Deconstructing shocks and persistence in OECD real exchange rates1)
  11. A contribution to the empirics of welfare growth
  12. Development accounting with wedges: the experience of six European countries
  13. Implementation cycles, growth and the labor market
  14. International technology adoption, R&D, and productivity growth
  15. Bequest taxes, donations, and house prices
  16. Business cycle accounting of the BRIC economies
  17. Privately optimal severance pay
  18. Small business loan guarantees as insurance against aggregate risks
  19. Output growth and unexpected government expenditures
  20. International business cycles and remittance flows
  21. Effects of productivity shocks on hours worked: UK evidence
  22. A prior predictive analysis of the effects of Loss Aversion/Narrow Framing in a macroeconomic model for asset pricing
  23. Exchange rate pass-through and fiscal multipliers
  24. Credit demand, credit supply, and economic activity
  25. Distortions, structural transformation and the Europe-US income gap
  26. Monetary policy shocks and real commodity prices
  27. Topics
  28. News-driven international business cycles
  29. Business cycle dynamics across the US states
  30. Required reserves as a credit policy tool
  31. The macroeconomic effects of the 35-h workweek regulation in France
  32. Productivity and resource misallocation in Latin America1)
  33. Information and communication technologies over the business cycle
  34. In search of lost time: the neoclassical synthesis
  35. Divorce laws and divorce rate in the US
  36. Is the “Great Recession” really so different from the past?
  37. Monetary business cycle accounting for Sweden
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