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Between Institutions and Global Forces: Norwegian Wage Formation Since Industrialisation^{ †}

^{1}

^{2}

^{†}

*Macroeconomics and Policy Making*, arranged in honour of Asbjørn Rødseth, 18 May, 2016, by the Department of Economics, University of Oslo. Thanks to Olav Bjerkholt for comments, and for showing me the article written by Frisch about “rational wage policies”, and the correspondence with Haavelmo that it led to. Discussions at the Workshop in econometrics at Statistics Norway, 21 October 2016, were also very useful, thanks to the participants. Thanks also to Jan Morten Dyrstad, David F. Hendry , Steinar Holden, Tord S. Krogh and Mikkel Myhre Walbækken for important comments and suggestions. Finally, thanks to the editors and to two anonymous referees for their comments, both critical and constructive. The numerical results in this paper were obtained by the use of

*OxMetrics 7/PcGive 14 and Eviews 9.5*.

## Abstract

**:**

In the days of Manchester liberalism, the wage contract was a matter between the individual worker and employer. Any “wage policies”, either by the society or by the organizations, were non-existent. Luckily, this has been changed.Ragnar Frisch (Arbeiderbladet 30 August 1945) [1].

## 1. Introduction

## 2. A Century Plus of Labour Market Change

#### 2.1. The Norwegian Economy at the Start of the 20th Century

#### 2.2. The End of Mass Emigration

#### 2.3. Unemployment and Productivity

#### 2.4. Labour Market Regulation

#### 2.5. Coordination

#### 2.6. Development of Working Time and Wages

## 3. Modelling: Theory

#### 3.1. Theory of Wages and the Development of Wage Modelling

At the same time as we find it challenging to determine wages theoretically, we also observe that actual wage bargains are struck year after year, and that they are rationalized by considerations of profits, actual and required (to attract investments), cost of living and relative wages (fairness). These observed regularities, that were documented early by for example Dunlop (1944) [65], give reason to believe that wage formation can be subject to econometric treatment.[wage formation]...depends on psychology, politics, and thousands of other intangible factors. As far as the economist is concerned, the final outcome is indeterminate—almost as indeterminate as the haggling between two millionaires over the price paid for a rare oil painting.

#### 3.2. Change and Continuity

#### 3.3. A Dynamic Model for Trends in Wage-and-Price Setting

#### 3.3.1. Nominal and Real Trends

#### 3.3.2. Wage-Price Spiral

#### 3.3.3. VAR Formulation

#### 3.3.4. Conditions for Global Asymptotic Stability

#### 3.3.5. Numerical Simulation of the Theory Model

## 4. Empirical Models

#### 4.1. Robust Estimation with Structural Breaks

#### 4.2. Reduced form VAR and Long-Run Wage Equation

#### 4.3. Single-Equation Modelling

#### 4.4. Multiple-Equation Modelling

#### 4.4.1. Identificaton of Wage and Price

#### 4.4.2. Reduced Form Estimates

#### 4.4.3. FIML Estimates of Structural Model

#### 4.5. Simulation and Closing of the Model

#### 4.6. Constancy and Invariance of the Coefficients of the Wage Equation, Lucas Citique

## 5. Summary and Discussion

## Conflicts of Interest

## Appendix A. Data Definitions and Sources

## Wages Level

## Consumer Price Index

**Figure A1.**The annual wage rate from Norges Bank’s Historical Monetary Data, ${W}^{NB}$ and from the annual national accounts, ${W}^{NR}$.

## Price Indices for Imports and GDP

## Price Index, Mainland Norway GDP

## GDP Fixed Prices

## GDP Fixed Prices per Capita

## Man-Hours for Mainland Norway

## GDP Fixed Prices for Mainland Norway

## Man-Years for Mainland Norway

## GDP per Man Hour for Mainland Norway

**Figure A2.**Labour productivity (GDP per man hour, Mainland-Norway) and productivity growth in Bergeaud, Cette and Lecat, BCL.

## GDP per Man Hour (Wage Earners) for Mainland Norway

## GDP per Man-Year for Mainland-Norway

## Payroll-Tax Rate

## Unemployment Rate

## Number of Working Days and Length of the Working Week

## Working Hours Lost in Labour Conflicts

^{1.}Ragnar Frisch was professor at the University of Oslo from 1931 to 1965, a founder of The Econometric Society and was awarded the first Nobel Prize in economics in 1969. Frisch seems to have been deeply influenced by observing at close range the impact of deflationary policies in Norway in the 1920s and by the Great Depression in the 1930s. His scientific work was motivated by the need for social improvements as much as an intellectual interest, Bjerkholt (2014) [2] (p. 299) and Bjerkholt and Qin (2011) [3] (p. 11). All quotes from the newspaper article (and the correspondence that it led to) have been translated by the author.^{2.}Frisch’s newspaper article is interesting also because it led to a correspondence with his pre-war assistant and colleague Trygve Haavelmo, who was still in USA, where he had been exiled during the war. Haavelmo opened by saying that he was “very interested in the problems” that Frisch had analysed in the article, and then went on to present a detailed note with comments (and improvements). Frisch, who wanted Haavelmo to come back to the University of Oslo, wrote back with enthusiasm and said that it was of the “greatest importance” that Haavelmo committed himself intellectually to this “all important field”, the theory of rational wage setting.^{3.}See Olstad (2009) [4], in particular chapter 5, and the concluding chapter.^{4.}Britain is an interesting case for historical comparison. At the time when the industrial unrest of the late 1960s was more of a nuisance than an unmanageable problem, Labour party minister Barbara Castle became frustrated by the unions’ lack of understanding that living in a liberalised market economy had consequences for how the unions could act. She mothered the ill fated White Paper In place of Strife in 1969, which in retrospect defined a turning point in the history of labour market regulation in Britain, see Sandbrook (2006) [5] (pp. 709–710).^{5.}The number is for 1903 which is the earliest year with data, cf. Appendix A.^{6.}Fixed 1990 International Geary-Khamis dollars, Maddison project database: http://www.ggdc.net/maddison/maddison-project/data.htm.^{7.}Norway left the Gold standard in 1914, even though it was a neutral country with no war efforts to finance, cf. Lie (2012) [15] (pp. 32,33). Norges Bank’s monetary expansion during the first two years of the war was related to international trade flows. However, during the two last war years another part of the monetary expansion was result of credit to domestic borowers, Værholm and Øksendal (2010) [16].^{8.}There was more than 25,000 immigrants in total in 1917, while only 2500 left Norway, Søbye (2014) [14] (Tables 4 and 15).^{9.}The Norwegian economy was affected by the Korean war of 1951–1952, but mainly in the form of a spurt of imported inflation, SSB (1965) [20] (pp. 385–392). The increase in unemployment in 1957 and 1958 may have been jointly caused by weak development in export markets, and unintended deflationary effects of fiscal policy, SSB (1965) [20] (pp. 406–408). The increase in unemployment in 1983 and 1984 had background in the weak development of the international economy and structural problems in Norway. It was first tackled by expansionary fiscal policy, which however was switched-off, primarily because the projected international recovery did not materialize. The large balance of payment deficits in the period with expansionary policy gave rise to concern about a possible loss of “economic scope for maneuvre”, SSB (1985) [21] (p. 97).^{10.}See Lie (2012) [15] (pp. 15–23).^{11.}The increased number of labour disputes, also illegal (“wild cat”) strikes, in the 1960s and 1970s is often seen as a “British disease”. However, in the 1960s and 1970s United Kingdom finished a mere seventh and sixth in a league table of working days lost per 1000 workers, with Canada, Italy, Australia, United States and Ireland all recording more strikes in those two decades. Even during the 1980s, United Kingdom finished third, behind Canada and Australia, cf. Wrigley (2002) [25] (Table 4.4), Sandbrook (2011) [26] (p. 98).^{12.}The data used by Bårdsen and Klovland is a panel data set of individual firms.^{13.}Olstad (2009) [4] (p. 419).^{14.}Reiersen (2015) [30] is an interesting analysis of the mental re-orientation during the 1920s and 1930, which probably was needed on both sides in order to break the deadlock marked by strife and industrial unrest. Reiersen’s view is that the main step was to move from a situation of distrust, and hence conflict as the main strategy on both sides, to a situation with sufficient trust so that the mutual strategy became one of compromise and cooperation.^{15.}As the interesting spat between Sæther and Eriksen (2014) [32] and Bjerkholt (2014) [2] shows, the “economic planning” of Norwegian post-war economy may have been misunderstood by some commentaries, or wrongly presented, as directives. The plans set out in the annual National Budget were expectations and intentions, not directives, Bjerkholt (2014) [2] (p. 301). The outcome depended on the international development in particular, as well as on economic control measures. In the early reconstruction years, the monitoring of the economy took place at a detailed level, and so did the use of control measures. However, the approach was more a reflection of pragmatism and an unorthodox view on policy instruments, than a principal position against product market liberalisation and consumer sovereignty SSB (1965) [20] (pp. 369,370).^{16.}The TCC had its origin in two important reports from 1966 about the system of wage and income formation, which we refer to in Section 2.5, see Longva (1994) [33].^{17.}In the period 1980–2010, Denmark, Finland and Sweden had higher union densities well above 70% for most of the time.^{18.}Again there may be an interesting parallel to Germany, where employer organisations were instrumental in operating the system of pattern bargaining, Soskice (1990) [39] (pp. 43–46).^{19.}An example of the relevance of this point is found in the contentious issues in shipyards’ regulation and the “STX-case”, where EFTA court advisory has collided with the Norwegian High Court domestic conception of public policy, see Evju (2014) [27].^{20.}On the role of the main-course model in Norwegian economic planning, see Bjerkholt (1998) [45].^{21.}Forder (2014) [42] (p. 31).^{22.}Hatton (1988) [72] (p. 84) concluded along the same lines for the British labour market: It did not change from “one where wages were set by atomistic competition to one in which the process was entirely institutional. Institutional wage setting was well established before 1914, though it became increasingly centralized until the late 1960s”.^{23.}We do not introduce explicit notation for firms’ expected wage, because with zero mean $I\left(0\right)$ expectation errors, it will not have any implications for co-integration (or not) between the variables. However, it is understood that ${w}_{t}$ in (4) is an expected variable, and that p and q in (5) likewise denote expected prices in this context.^{24.}For the coefficients ${\psi}_{wq}$, ${\psi}_{qw}$ and ${\psi}_{wp}$, ${\psi}_{qpi}$, the non-negative signs are standard in economic models. Negative values of ${\theta}_{w}$ and ${\theta}_{q}$, can give rise to explosive dynamics in wages and prices (hyperinflation), which is different from the low to moderately high inflation scenario that we have in mind for this paper.^{25.}Later theoretical derivations in the literature, using the Nash-solution, agree that ${\theta}_{w}>0$ is implied by collective bargaining, but also find $\omega =0$ to be equally theoretically important, and even purge the compensation for cost-of-living increases from the short-run dynamics, see Forslund et al. (2008) [82].^{26.}An alternative is to define a “productivity corrected producer real wage”: $r{w}_{t}^{fc}=r{w}_{t}^{f}-\iota =1{a}_{t}$^{27.}Since ${a}_{t}$ is included as unrestricted, $\mathbf{R}$ has four columns, against three in the theoretical section. The VAR includes an unrestricted constant and a restricted trend. The ${H}_{0}$ of no cointegration is rejected at the 1 percent level using the trace-test and the critical values in Table 13 in Doornik (2003) [92]. Also the hypothesis of one cointegrating vector against the alternative of two can be formally rejected. Accepting two long-run relationships, the joint hypothesis that the trend has zero coefficients in both co-integration relationships cannot be rejected at the 1 percent level.^{28.}In the IV column the Likelihood-ratio test statistic for the restriction ${\theta}_{w}=0$ becomes ${\chi}^{2}\left(1\right)=$ $5.59\left[0.018\right]$ with p-value i brackets. The OLS results are: ${\chi}^{2}\left(1\right)=14.31\left[0.0002\right]$.^{29.}That is, the joint hypothesis of ${\theta}_{w}=0$ and the coefficients of the three nominal growth rates summing to one.^{30.}Corresponding to ${\psi}_{wq}+{\psi}_{wp}=1$ in the theoretical model.^{31.}Their Equation (21).^{32.}As long as the covariance matrix of the disturbances (which are omitted in the notation for simplicity) is unrestricted.^{33.}The first test (marking the start of the graph) tests the stability of the relationship over the period from 1926 to 2015. The second uses data to 1926 for estimation, and tests stability over the 1927–2015 period. Hence the number of out-of-sample periods are decreasing as we move from left to right along this graph.^{34.}Holden and Nymoen (2002) [110] concluded on the basis of results for Denmark, Finland, Norway and Sweden, for samples that started in the early 1960s and ended in 1994^{36.}Column labelled “Sysselsatte personer” in “Vedlegg 2 Table, page 35–37.^{37.}The numbers are revised, not much, compared to Grytten (1995) [118].^{39.}Galenson and Zellner (1957) [121], who included Norway in their comparison of unemployment data, used this source for a longer period of data.^{40.}“Norge hører til de land som har hatt bort imot permanent full sysselsetting i nesten hele etterkrigstiden, og der konjunkturelle bølgebevegelser produksjon og sysselsetting har vært lite merkbare ” SSB (1965) [20] (p. 352).

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**Figure 1.**Emigration in percent of the Norwegian population. Source: Søbye (2014) [14] (Table 15).

**Figure 2.**The rate of unemployment cf. Appendix A, together with empirical breaks in mean and labels for major events.

**Figure 3.**Labour productivity (LP), measured as GDP in fixed prices in Mainland-Norway per hour worked in Mainland Norway, and the rate of unemployment. Source: Appendix A. LP is a centered moving average using one period lead and one period lag, the raw series is shown in the data appendix.

**Figure 4.**Hours lost in industrial unrest in percent of hours worked and the absenteeism percent. Source: Appendix A.

**Figure 5.**Working days in the year, and the length of the working week. 1900 = 1. Source: Appendix A.

**Figure 6.**Annual growth in annual wage and in consumer price index (CPI). Source: Appendix A.

**Figure 7.**Annual change in the import price index, together with annual wage change and consumer price inflation. Source: Appendix A.

**Figure 8.**15 year real wage growth percentages from 1900 to 2015, for example, the height of the first bar shows that real wage growth from 1885 to 1900 was 25 percent, and the last bar shows that growth in the real wage from 2000 to 2015 was close to 40 percent. Source: Appendix A.

**Figure 9.**The consumer real wage and labour productivity, logarithmic scale. The real wage graph has been shifted down for easier comparison with the productivity graph. Source: Appendix A.

**Figure 10.**Solution paths for endogenous variables shown in graphs with dashed lines, together with “actuals” (the computer generated time series) and 95 percent uncertainty intervals. The first solution period is period 125 and the final period of the dynamic simulation is number 200.

**Figure 11.**Solution paths for endogenous variables shown in graphs with dashed lines, together with “actuals” (the computer generated time series) and 95 percent uncertainty intervals. The first solution period is period 125 and the final period of the dynamic simulation is number 200.

**Figure 13.**Dynamic simulation of the FIML estimated model in (27), conditional on observed time series of ${a}_{t}$ and $p{i}_{t}$.

**Figure 14.**The solutions for wage growth ($\mathrm{\Delta}wc$) and unemployment (u) shown together with their (within equation) indicator variables.

**Figure 15.**Dynamic simulation of the Full Information Maximum Likelihood (FIML) estimated model in (27), extended by equations for $\mathrm{\Delta}{a}_{t}$ and $\mathrm{\Delta}p{i}_{t}$, and actuals. Simulation starts in 1905.

**Figure 16.**15 year real wage growth percentages, actuals and simulated from FIML estimated multiple-equation model, with ${a}_{t}$ and $p{i}_{t}$ as additional endogenous variables in the model.

Unionization Rate | Employer Organization | |
---|---|---|

1948 | 50% | |

1972 | 51% | |

1990 | 57% | 50 % |

2005 | 53% | 60 % |

2013 | 52% | 65 % |

**Table 2.**Coverage rates in Norway in selected years. (Source: Nergaard (2014) [38] (Table 2.5)).

Private Sector | Production of Goods | Service | |
---|---|---|---|

1998 | 63% | 71% | 58% |

2004 | 60% | 63% | 58% |

2005 | 59% | 64% | 56% |

2008 | 59% | 65% | 55% |

2013 | 58% | 62% | 56% |

**Table 3.**Empirical versions of the wage equation in (11) in the theory model. $\widehat{\sigma}$ denotes the estimated residual standard error. The standard test for residual mis-specification (autocorrelation, heteroskedasticity and non-normality) are insignificant in the two models reported.

OLS | GIVE | ||
---|---|---|---|

$\mathrm{\Delta}{p}_{t}$ | $\underset{}{0.53}$ | $\underset{}{0.44}$ | |

(0.03) | (0.11) | ||

$\mathrm{\Delta}{u}_{t}$ | $\underset{}{-0.01}$ | $\underset{}{-0.05}$ | |

(0.005) | (0.03) | ||

$\mathrm{\Delta}{a}_{t}$ | $\underset{}{0.25}$ | $\underset{}{0.17}$ | |

(0.03) | (0.074) | ||

$\mathrm{\Delta}{p}_{t-1}$ | $\underset{}{0.21}$ | $\underset{}{0.27}$ | |

(0.04) | (0.04) | ||

$\mathrm{\Delta}tax$ | $\underset{}{0.89}$ | $\underset{}{0.94}$ | |

(0.26) | (0.26) | ||

$\mathrm{\Delta}w{c}_{t-1}$ | $\underset{}{0.11}$ | $\underset{}{0.15}$ | |

(0.04) | (0.04) | ||

${(wc-q-a)}_{t-1}$ | $\underset{}{-0.08}$ | $\underset{}{-0.06}$ | |

(0.02) | (0.03) | ||

${u}_{t-1}$ | $\underset{}{-0.01}$ | $\underset{}{-0.01}$ | |

(0.002) | (0.003) | ||

Constant | $\underset{}{0.56}$ | $\underset{}{0.47}$ | |

(0.14) | (0.19) | ||

$wbrea{k}_{t}$ | $\underset{}{0.98}$ | $\underset{}{0.96}$ | |

(0.06) | (0.08) | ||

Sample: 1905–2015 | |||

$\widehat{\sigma}100$ | $1.38$ | $1.72$ | |

Sargan IV-test | ${\chi}^{2}\left(3\right)=2.56$ | ||

$\mathrm{\Delta}{a}_{t-1,}\mathrm{\Delta}{q}_{t-1}$, $\mathrm{\Delta}{q}_{t-1},\mathrm{\Delta}{u}_{t-1}$,$\mathrm{\Delta}n{h}_{t}$ |

$\mathbf{\Delta}{\mathit{w}}_{\mathit{t}}$ | $\mathbf{\Delta}{\mathit{q}}_{\mathit{t}}$ | $\mathbf{\Delta}{\mathit{p}}_{\mathit{t}}$ | $\mathbf{\Delta}{\mathit{u}}_{\mathit{t}}$ | |
---|---|---|---|---|

$\widehat{\sigma}100{\phantom{\rule{0.166667em}{0ex}}}^{\u2020}$ | $1.48$ | $2.04$ | $1.56$ | $0.22$ |

w-p ecm ${}^{\u2021}$ ${\chi}^{2}\left(2\right)$ | 5.5 * | 30.8 ** | 17.8 * | $1.1$ |

Breaks ${\chi}^{2}\left(4\right)$ | 207 ** | 254 ** | 340 ** | 34 ** |

Vector mis-spesification tests: | ||||

${F}_{AR}(33,307)$ | $1.4$ | |||

${\chi}_{N}^{2}\left(8\right)$ | $11.5$ | |||

${F}_{Het}(128,301)$ | 1.8 ** |

**Table 5.**Estimated residual standard errors, and tests of ${\theta}_{w}=0$ and ${\theta}_{q}=0$ in the structural wage and price equations.

$\mathbf{\Delta}{\mathit{w}}_{\mathit{t}}$ | $\mathbf{\Delta}{\mathit{q}}_{\mathit{t}}$ | |
---|---|---|

${\widehat{\sigma}}^{2}100$ | $1.43$ | $1.90$ |

W-P ECM ${}^{\u2021}$ ${\chi}^{2}\left(1\right)$ | 16.1 ** | 33.2 ** |

**Table 6.**Split sample (1935) and full sample estimates (OLS) of the wage equation (with ${u}_{t}$ replacing the two terms $\mathrm{\Delta}{u}_{t}$ and ${u}_{t-1}$). The standard test for residual mis-specification (autocorrelation, heteroscedasticity and non-normality) are insignificant in all three samples.

1904–1934 | 1935–2015 | 1904–2015 | |
---|---|---|---|

$\mathrm{\Delta}{p}_{t}$ | $\underset{}{0.55}$ | $\underset{}{0.46}$ | $\underset{}{0.53}$ |

(0.06) | (0.06) | (0.03) | |

$\mathrm{\Delta}{a}_{t}$ | $\underset{}{0.26}$ | $\underset{}{0.21}$ | $\underset{}{0.26}$ |

(0.08) | (0.06) | (0.03) | |

$\mathrm{\Delta}{p}_{t-1}$ | $\underset{}{0.24}$ | $\underset{}{0.19}$ | $\underset{}{0.21}$ |

(0.08) | (0.07) | (0.04) | |

$\mathrm{\Delta}tax$ | $\underset{}{0.78}$ | $\underset{}{1.01}$ | $\underset{}{0.89}$ |

(2.67) | (0.21) | (0.20) | |

$\mathrm{\Delta}w{c}_{t-1}$ | $\underset{}{0.07}$ | $\underset{}{0.21}$ | $\underset{}{0.12}$ |

(0.06) | (0.07) | (0.03) | |

${(wc-q-a)}_{t-1}$ | $\underset{}{-0.06}$ | $\underset{}{-0.06}$ | $\underset{}{-0.08}$ |

(0.05) | (0.03) | (0.02) | |

${u}_{t}$ | $\underset{}{-0.01}$ | $\underset{}{-0.01}$ | $\underset{}{-0.01}$ |

(0.008) | (0.002) | (0.002) | |

Constant | $\underset{}{0.43}$ | $\underset{}{0.42}$ | $\underset{}{0.52}$ |

(0.30) | (0.27) | (0.14) | |

$wbrea{k}_{t}$ | $\underset{}{1.00}$ | $\underset{}{0.91}$ | $\underset{}{0.97}$ |

(0.11) | (0.10) | (0.06) | |

$\widehat{\sigma}100$ | $1.63$ | $1.32$ | $1.37$ |

Chow test | $F(20,92)=0.24\left[0.99\right]$ |

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Nymoen, R. Between Institutions and Global Forces: Norwegian Wage Formation Since Industrialisation. *Econometrics* **2017**, *5*, 6.
https://doi.org/10.3390/econometrics5010006

**AMA Style**

Nymoen R. Between Institutions and Global Forces: Norwegian Wage Formation Since Industrialisation. *Econometrics*. 2017; 5(1):6.
https://doi.org/10.3390/econometrics5010006

**Chicago/Turabian Style**

Nymoen, Ragnar. 2017. "Between Institutions and Global Forces: Norwegian Wage Formation Since Industrialisation" *Econometrics* 5, no. 1: 6.
https://doi.org/10.3390/econometrics5010006