Do increases in public sector wages affect inflation?*

Ozana Nadoveza**

Ozana Nadoveza

Affiliation: Croatian National Bank, Zagreb, Croatia ; University of Zagreb, Faculty of Economics and Business, Zagreb, Croatia

0000-0002-3651-7795

Correspondence
onadoveza@efzg.hr

Article   |   Year:  2025   |   Pages:  1 - 44   |   Volume:  49   |   Issue:  1
Received:  June 1, 2024   |   Accepted:  October 27, 2024   |   Published online:  March 10, 2025

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https://doi.org/10.3326/pse.49.1.1

Abstract

1 Introduction

2024

Graph 1

Wages, productivity and inflation

DISPLAY Graph

Before the first estimates of the impact of the sharp rise in total wages on inflation and the inflation differential (which began to ease in late 2023 and early 2024) were published, the decision to implement a substantial wage increase as part of the civil and public service wage reform reignited discussions about the potential inflationary effects of rapid wage growth³. According to the government document titled Reform in Numbers (Government of RC, 2024), this reform affects 244,000 state and public service employees, aiming to streamline and equalize job classifications by merging roles of similar complexity based on evaluations and reducing the number of job titles. Of the five phases in this reform, the most relevant here is the 15% wage increase resulting from coefficient adjustments effective from March 2023.

Public sector wage growth can impact inflation through several channels. The direct effect stems from a possible rise in public service prices, driven by higher employee costs, as labour compensation accounts for over 80% of the gross value added (GVA) in the public sector⁴, according to Eurostat’s national accounts data. This is significantly higher than the average employee compensation share of approximately 50% in other sectors. However, this direct impact is likely small because (a) public sector prices are mostly set outside the market, making the pass-through of wage growth to public service prices lower than in other sectors, and (b) services that consumers purchase directly from the public sector represent a small portion of the overall consumer basket. Nonetheless, substantial wage increases in the public sector may create inflationary pressures indirectly by increasing the aggregate demand of public sector employees and potentially influencing private sector wages. The size of this indirect effect will depend on the proportion of public sector employment within the economy and the degree of wage spillover from the public to the private sector. Thus, a larger public sector could amplify these indirect inflationary effects.

This paper seeks to estimate both the direct and the indirect inflationary effects of public sector wage growth using a methodology based on Bayesian VAR models with sign and zero restrictions on impulse response functions, which approximate the standard wage-setting (WS) and price-setting (PS) model. By employing this established approach to analyse the impact of wage growth on prices, the paper contributes to academic literature by introducing a novel framework for identifying and examining the direct and indirect effects of public sector wage growth on inflation. Additionally, the paper adds to the ongoing policy and economic debate regarding the potential inflationary impact of exceptionally high wage increases in the public sector.

Analysis of the results of model estimates based on data for Croatia from 2004 to 2023 shows that wage growth in the public sector has a negligible direct but a relatively strong potential indirect impact on overall inflation. Thus, wage growth in the public sector increases the total inflation rate through the direct channel by approximately 0.15 percentage points. The negligible direct effect is mostly the result of the small share of public sector services in the consumer basket. On the other hand, it is estimated that the total indirect impact on inflation could be relatively strong and amount to between 0.34 and 0.88 percentage points, depending on the assumed contribution of wage growth in the public sector to total aggregate demand and the extent of spillover of wage growth in the public sector to the private sector. However, it is important to emphasize that considering the assumptions about the spillover of wage growth to the private sector and aggregate demand, bearing in mind that this wage growth is in the double digits, we can conclude that the estimated total contribution of wage growth in the public sector of 0.5 pp – 1 pp is relatively low. However, despite the relatively low estimated contribution of wage growth in the public sector to inflation, these results should be interpreted with caution, since empirical assessment of the impact of wage growth on inflation is inherently complex. That is, apart from the fact that the relationship between wages and prices is bidirectional (Conti and Nobili, 2019; Ivanac, Kunovac and Nadoveza,2024), its strength and direction depend on the nature of the shocks affecting the economy (Bobeica, Ciccarelli and Vansteenkiste, 2019, 2021; Conti and Nobili, 2019; Ivanac, Kunovac and Nadoveza,2024), so it is difficult to estimate empirically the real causal effect of wage growth on prices – even without additional assumptions regarding the potential effects of public sector wage growth on aggregate demand and private sector wages.

The remainder of the paper is organized as follows: section 2 provides a summary of the relevant theoretical and empirical literature. Section 3 outlines the data and methodology used to assess the effects of public sector wage growth on inflation. Section 4 presents the empirical results, and section 5 discusses the main conclusions and limitations of the estimates provided in the paper.

2 Exploring the relationship between wages and prices: insights from existing literature

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2.1 Theoretical framework

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A formal framework for understanding the joint dynamics of wage and price movements is captured in a basic wage-setting (WS) and price-setting (PS) model, as outlined by Blanchard and Bernanke (2023).

∆wt = ∆pet - α(ut - u*) + ∆αLt

(1)

where Δw_t = w_t – w_t–1 is the rate of change of nominal wages in time t, ∆p^e_t = p^e_t - p_t-1 is the expected rate of inflation in time t, u_t is the unemployment rate in time t, and u^* is the natural rate of unemployment in time t, ∆α_Lt is the real (or expected) labour productivity growth rate. Equation (1) indicates that workers’ wage demands are driven by their inflation expectations and the current labour market conditions. When the unemployment rate is low, workers have greater bargaining power since employers face challenges in filling vacant positions, allowing workers to negotiate for higher nominal wages.

Also, when workers expect higher inflation, they demand higher wages to prevent real wages from falling. The way in which workers form inflation expectations can be described as follows:

∆pet = λΔp*t - (1-λ)Δpt-1

(2)

Here, ∆p^*_t represents the long-term expected inflation rate, typically aligned with the central bank’s target inflation rate. It is assumed that long-term inflation expectations are shaped by last year’s long-term inflation and the inflation rate from the previous period.

∆p*t = δΔp*t-1 - (1-δ)Δpt-1

(3)

The parameter λ in equation (2) indicates the anchoring of short-term expectations, and the parameter δ in equation (3) indicates the anchoring of long-term expectations. When expectations are fully anchored, both parameters are equal to 1, and when expectations are completely unanchored, they are equal to 0⁸. 

In addition to expected inflation and labour market conditions, nominal wage growth described by equation (1) is also influenced by factors such as the actual or anticipated growth rate of labour productivity (∆a_Lt). In theory, prices increase according to the growth rate of unit labour costs rather than wages alone. Consequently, any changes or adjustments that affect labour productivity can mitigate the impact of wage growth on prices. For instance, companies may respond to wage increase demands by reducing their workforce, which might increase labour productivity. With higher labour productivity, unit labour costs may rise more slowly than wages, thereby reducing the sensitivity of prices to wage changes. Additionally, if layoffs lead to higher unemployment, total demand may decrease, potentially exerting downward pressure on prices. 

The approach producers take to set prices is generally described by the price-setting (PS) relationship:

∆pt = ∆wt - ∆αLt + ∆zt

(4)

In equation (4), z_t represents all factors that influence pricing beyond unit labour costs – defined as wage growth (w) minus labour productivity growth (α_L). These factors include mark-ups and costs of intermediates, such as the prices of energy, food, and other raw materials. Together, these relationships form the basis of the standard Phillips curve, which is commonly used to analyse the mechanism through which wage increases translate into price changes.

∆pt = λ∆p*t - (1 - ∆pt-1 - α(ut - u*) + ∆zt

(5)

The Phillips curve describes aggregate supply, illustrating how price levels move based on expected inflation, labour market conditions, and other factors. Assuming the Phillips relationship holds, equation (5) suggests that price dynamics are influenced by the anchoring of inflation expectations, labour market conditions which affect wage demands, and fluctuations in mark-ups and prices of important intermediates, such as energy and other raw materials.

A significant empirical challenge in assessing the impact of wages on prices (especially in the short and medium term) arises from the simultaneous determination of wages and prices, as evident in the WS-PS model (Conti and Nobili, 2019). The wage-price relationship is bidirectional, making it difficult to pinpoint and quantify the causal impact of wages on prices. The co-movement of prices and wages can be driven by (a) demand shocks, (b) supply shocks, or (c) the attempts of workers or producers to increase their share in income distribution (Blanchard, 1986). The strength of the wage-price link depends on the nature of the shock. For instance, research shows that under a positive aggregate demand shock, the connection between wages and prices is much stronger than in the case of a supply shock⁹.

A positive aggregate demand shock is characterized by rising prices and income, leading to increased demand for labour and a drop in the unemployment rate below its natural level. Companies respond to heightened demand for products by raising prices (demand-push), while workers, in response to increased demand for labour, push for higher wages. Wage growth raises production costs (cost-push), prompting further price increases unless mark-ups or input costs change. This cycle of rising prices and wages continues until income stabilizes at its potential level, or until unemployment returns to a level that does not accelerate inflation¹⁰, as seen in equations (1) and (5).

Conversely, a negative aggregate supply shock is marked by rising prices alongside declining income. When such an inflationary shock occurs, workers seek wage increases to maintain their real purchasing power. However, a negative supply shock also raises the natural unemployment rate (or lowers the potential output), thereby weakening workers’ bargaining power due to the availability of the involuntarily unemployed labour force in the market. As the economy adjusts to a higher equilibrium unemployment rate and lower potential output, aggregate demand declines, which puts a downward pressure on prices. Thus, in the case of a supply shock, wage growth impacts prices mainly through the cost-push channel, and this effect is mitigated (or even offset) by the reduction in aggregate demand.

2.2 Empirical framework

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The findings of various studies offer different assessments of the wage-to-price passthrough. While most research suggests a weak or partial transmission of wage increases to prices (Bobeica, Ciccarelli and Vansteenkiste, 2019, 2021; Conti and Nobili, 2019; Hahn, 2020; Blanchard and Bernanke, 2023; Arce et al., 2024), where only a portion of wage increases is passed on to prices due to competitiveness gains and changes in mark-ups (see, for instance, Deutsche Bundesbank, 2019; Bobeica, Ciccarelli and Vansteenkiste, 2019), some studies indicate that the extent of transmission varies across sectors and countries (Bobeica, Ciccarelli and Vansteenkiste, 2019).

More recent research typically analyses the wage-price nexus using structural VAR models similar to the approach taken in this paper. These models are able to account for shock-dependent wage-to-price relationship¹¹ (e.g., Gumiel and Hahn, 2018; Galí and Gambetti, 2019; Conti and Nobili, 2019; Bobeica, Ciccarelli and Vansteenkiste, 2019, 2021; Hahn, 2020), and offer a reasonable approximation of the WS-PS model. The results of these studies generally show that the wage-price relationship is strongest during aggregate demand shocks, but weaker during labour market shocks, and even negative in the case of aggregate supply shocks. Furthermore, Bobeica, Ciccarelli and Vansteenkiste (2019, 2021), and Ivanac, Kunovac and Nadoveza (2024) investigate the role of wages in transmission of various structural shocks to prices using a counterfactual scenario within a VAR framework¹². These studies find that wages significantly amplify the effects of aggregate demand shocks on inflation, suggesting that, without wage growth, inflation would be considerably lower during aggregate demand shocks. In contrast, the role of wages in transmitting aggregate supply shocks to prices is much less significant.

In addition to the VAR model, Blanchard and Bernanke (2023) present a simple dynamic model of wages, prices (WS-PS), and short- and long-term inflation expectations, which was later replicated for the euro area by Arce et al. (2024). Their findings suggest that wage growth had a relatively low impact on inflation during the period of heightened inflation that began in late 2021 and that the surge in inflation during this period was primarily driven by shocks in raw material prices.

While this paper draws heavily on the literature that combines zero and sign restrictions on impulse response functions within the VAR framework to analyse the relationship between wages and prices, it makes two notable contributions. First, in addition to examining the conditional correlation between wages and prices under various structural shocks (wage-to-price multipliers), the paper explores time-varying correlations between wages and prices in both the public sector and in the overall economy. As in Ivanac, Kunovac and Nadoveza (2024) this analysis shows how the dynamics of wages and prices evolves over time even without a time-varying parameter. Second, the paper identifies the potential role of public sector wages in the transmission of various shocks to inflation, both across the economy and within the public sector, by using wage-to-price multipliers (Bobeica, Ciccarelli and Vansteenkiste, 2019, 2021; Conti and Nobili, 2019; Ivanac, Kunovac and Nadoveza, 2024). This approach is rarely applied in the literature on wage-price transmission but has proven to be a valuable tool for quantifying the indirect effects of public sector wage growth on overall inflation. Lastly, the paper makes a significant professional contribution by using the standard methodology in an analysis of the wage-price relationship in the public sector – a relatively large and crucial sector in most countries – in which no studies have attempted to quantify the transmission of wages to prices.

3 Methodology and data

Prices and wages in both the public sector and the overall economy that are used in the empirical analysis are illustrated in graph 2¹⁴. The graph shows that wage trends in the public and private sectors are generally synchronised (graph 2a), with wage growth during the high inflation period of 2022 and 2023 (graph 3a) being exceptionally high. This surge can largely be attributed to the wage catch-up process aimed at preventing a significant decline in real wages during the high inflation period. On the other hand, inflation measured by the constructed HICP for public sector services (see appendix) did not always follow the dynamics of overall price growth, which is partly due to the role of administered prices in the price setting process for public sector services. The most notable divergence between total inflation and inflation in public sector services occurred in 2009, largely due to healthcare system reform, which introduced a new system of co-payments and supplementary health care insurance. Since, according to tables available in Cai and Vandyck (2020), healthcare spending accounts for a significant share (33.7%) of total consumer expenditure on public sector services, this reform had a marked impact on the constructed price index for public sector services.

The model used to estimate the impact of wage growth (in the public sector) on inflation (of public sector services) includes five key variables for the period from 2004Q1 to 2023Q4: real GVA and GDP (with GVA from the services sector covering O-Q sections¹⁵), HICP inflation¹⁶ (of public sector services, calculated using the CPA to COICOP conversion tables developed by Cai and Vandyck, 2020 ¹⁷), average wages (in the public sector)¹⁸, labour productivity¹⁹ and employment (in sections O-Q), and the unemployment rate. All variables are seasonally adjusted and expressed in quarterly growth rates, except for the unemployment rate, which is expressed in quarterly differences.

3.1 Identification of the effects of public sector wage growth on inflation

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Specifically, a positive demand shock is one that simultaneously boosts economic activity (measured by GVA and GDP), prices and wages. As economic activity rises, firms’ greater demand for capital and labour leads to a reduction in the unemployment rate (i.e., increases employment). In the short run, following Okun’s law, the effect on employment is smaller than the effect on economic activity, resulting in a rise in labour productivity. As a result, unit labour costs (wages adjusted for labour productivity) grow slower than wages. In addition to these short-run dynamics, it is assumed that economic activity does not respond to demand shocks in the long run, as standard macroeconomic theory assumes that demand shocks dissipate over time. Therefore, the long-term response of economic activity to demand shocks is assumed to be zero. On the other hand, a supply shock leads to increases in economic activity, labour productivity, and wages, while simultaneously reducing consumer prices and unemployment (i.e., increasing employment) (see, for example, Dedola and Neri, 2007; Peersman and Straub, 2009). In addition to these standard economic shocks, the model also identifies two shocks related to the labour market. A negative labour supply shock reduces labour force participation, which in turn lowers economic activity but also reduces the unemployment rate (increases employment). At the same time, wages and prices rise. This shock is differentiated from the aggregate demand shock by its distinct effect on economic activity. A wage mark-up shock, defined as an increase in the share of wages in the income distribution (wage growth²¹), raises wages while reducing producer profits (producer mark-ups). This increases marginal costs and inflation. Concurrently, the unemployment rate rises (employment decreases) as firms cut jobs due to higher hiring costs, and economic activity declines. In the case of labour market shocks in the economy-wide model, where we estimate the model using the unemployment rate, we remain neutral regarding the response of labour productivity. However, in the models estimated using employment, separating the two labour market shocks would not be possible without additional assumptions regarding the response of labour productivity to each shock. Thus, in the employment-based model, we assume that when wage markups increase, GDP rises more slowly than employment, leading to higher productivity. Conversely, when a labour supply shock occurs, productivity declines. The fifth (and final) shock in the model remains unidentified. The short-term restrictions discussed above are summarized in table 1. 

3.2 Methodology and assumptions for estimating the direct and indirect effects of public sector wage growth on inflation

(6)

In equation (6), IRF_h^HICPo-q represents the cumulative response of prices²³ to a one standard-deviation public sector mark-up shock over a given horizon. In this paper, we set h=4, which corresponds to one year after the shock occurs. shockW_t^O-Q indicates the magnitude of the public sector wage shock, expressed in standard deviations of the wage mark-up shock in the public sector model, while HICP_t^Wo-q refers to the share of public services in the consumer basket, based on the conversion tables from Cai and Vandyck (2020).

The estimation of the indirect effect of public sector wage growth on inflation that we propose in this paper is more complex and relies on a greater number of assumptions. To evaluate the indirect effect, we draw on the methodology used to calculate the wage-to-price multipliers (Bobeica, Ciccarelli and Vansteenkiste, 2019, 2021; Conti and Nobili, 2019; Ivanac, Kunovac and Nadoveza, 2024). The underlying idea is that exogenous, reform related, wage growth in the public sector, will stimulate aggregate demand and potentially spill over into wage growth in the private sector, creating shocks that could generate additional inflationary pressures. To estimate these effects, we first estimate a (B)VAR model for the entire economy, where we identify the same shocks as in the public sector model (demand, supply, and two labour market related shocks). This model allows us to examine the co-movements of prices and wages (labour costs) under the aggregate demand and wage mark-up shocks that could be triggered by exogenous public sector wage growth. We first estimate the strength of the wage mark-up shock resulting from the public sector wage growth shock at the economy-wide level. Then, using the wage-to-price multipliers for demand and wage mark-up shocks, we estimate the resulting effects on inflation.

(7)

In equation (7), represents the cumulative response of inflation to aggregate demand shocks in the overall economy model, while denotes the cumulative response of wages to an aggregate demand shock. ∆W_t^w refers to the change of wages under the wage mark-up shock resulting from the exogenous increase in public sector wages. It is calculated as a product of the cumulative impulse response function of wages to wage mark-up shock in the economy-wide model and the estimated size of wage mark-up shock expressed in standard deviations of the shock, i.e.:

(8)

We estimate the indirect effect of the public sector wage growth shock on inflation through its potential spillover to total wages in the same manner, specifically:

(9)

In equation (9),  represents the cumulative response of inflation to wage mark-up shock in the economy-wide model, while denotes the cumulative response of wages to a wage mark-up shock. As in equation (7), ∆W_t^w is given by equation (8) and represents the estimated wage growth in the overall economy resulting from the exogenous wage increase in the public sector. 

The total indirect effect of public sector wage growth on inflation is the weighted sum of these two indirect effects, specifically:

(10)

The equation (10) implies that we assume that the public sector wage growth, which indirectly impacts inflation through the aggregate demand channel, cannot concurrently affect inflation via a spillover to public sector wages, and vice versa. Therefore, α_AD + α_W = 1, or equivalently, α_W = 1 – α_AD, must always hold. Specifically, we assume that if some part of the increase in public sector wages spills over into the economy via the demand channel, we treat the rise in private sector wages as an endogenous result of the increased demand in the overall economy. Likewise, if some part of the increase in public sector wages spills over into the economy via private sector wages, we treat the increase in aggregate demand as an endogenous outcome of wage growth in both sectors. The total effect on inflation is calculated as the sum of the estimated direct effect and the total indirect effect.

4 Results

4.1 The relationship between wage growth and inflation in the public and private sectors

(11)

The results show that the positive relationship between wages and prices is particularly strong for aggregate demand shocks in both the public sector and the overall economy, wage growth being associated with 1.5 (economy-wide) to 2 (public sector) times stronger price growth in the short run (after one quarter, or h=1). This might suggest that public service prices tend to rise more significantly only during favourable economic conditions, such as periods of robust aggregate demand growth. The stronger relationship between wages and prices in the public sector during such times may be due to the higher share of labour costs (wages) in the public sector, which mainly produces services, compared to the other sectors in the economy. However, after a year (h>4), the relationship between wages and prices in the public sector closely resembles that in the overall economy.

However, the relationship remains relatively strong, which is consistent with findings from empirical studies (Bobeica, Ciccarelli and Vansteenkiste, 2019, 2021; Conti and Nobili, 2019; and Ivanac, Kunovac and Nadoveza, 2024). Additionally, under labour market related shocks, the wage-price relationship is only moderately positive in both the public and private sectors (cumulative wage-to-price shock-dependent multipliers are around 0.5). Conversely, in the case of aggregate supply shocks, the relationship between wages and prices is negative. This negative relationship is more pronounced in the public sector, in both the short run (-0.8 versus -0.2) and the long run (-0.35 versus -0.05). This may be due to public sector wage freezes during recessions, especially during the prolonged period when Croatia was under the Excessive Deficit Procedure (EDP), during which public sector wage growth was constrained regardless of inflationary pressures.

Graph 3

Shock dependent cumulative wage-to-price multipliers

DISPLAY Graph

The relationship between wage and price growth at any given point of time depends on the economic shocks that dominate wage dynamics, which in turn determine the ability of producers and service providers to pass on rising costs to consumers. This potential is clearly highest when wages are driven by aggregate demand shocks. Graph 4 shows that, after the first quarter of 2020, wage dynamics in the public sector were increasingly influenced by labour supply and aggregate supply shocks. This is likely related to technological changes and the digitalization of public services during the COVID-19 pandemic. In contrast, since 2022, wages in the entire economy have been primarily driven by exceptionally strong demand, which is probably at least partially related to the demand surge in tourism and the associated wage growth in the hospitality sector.

Graph 4

Relative importance of shocks in wage dynamics (2-year moving average)

DISPLAY Graph

 

As a result, the time-varying correlation between wage and price growth has been significantly higher in the overall economy than in the public sector in the recent periods (graph 5). This aligns with discussions on the potential effects of wage growth on inflation during periods of strong wage increases in Croatia, particularly in 2022 and 2023. It is also worth noting that the time-varying correlation between wage and price growth in the public sector is generally lower than in the overall economy. This is likely because public employees, when negotiating wage increases, do not typically take into account the rising prices of public services, but rather consider overall inflation during wage bargaining process.

Graph 5

Time-varying correlation between wage growth and inflation (2-year moving average)

DISPLAY Graph

4.2 Estimation of the effect of public sector wage growth on inflation

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5 Conclusion

Currently, there are no estimates of the potential effects of high public sector wage growth in 2024 on inflation. This gap in systematic estimates is partly due to the absence of a standard methodology for evaluating the impact of public sector wages on inflation. This is probably influenced by the prevailing view that the direct effect of public sector wage increases on inflation is small, given that public sector prices are non-market driven and make up a small share of the consumer basket (Whiteley, 2023). In this paper, we use the results of the methodology for analysing the wage to price pass-through to assess the potential impact of coefficient-reform-related public sector wage growth to headline inflation. We also provide an estimate of the overall impact that public sector wage growth in Croatia could have on inflation.

Appendix

To analyse the relationship between wages and prices in the public sector and the entire economy, we employ a Vector Autoregressive (VAR) model estimated using Bayesian techniques, based on data from Croatia spanning the period 2004Q1 to 2023Q4. Our estimation of the sign-restricted and zero-restricted Bayesian VAR model follows the methodology proposed by Arias, Rubio-Ramirez and Waggoner (2014). The procedure is outlined in detail by Deskar-Škrbić, Kotarac and Kunovac (2020), with their code adapted for the specific needs of this analysis. 

The SVAR model with i lags can be expressed as:

A0yt = μ + A1yt-1 + ⋯ + Aiyt-i+ εt, t = 1, …, T

(A1)

where y_t is an n × 1 vector of variables, A_j is an n × n matrix of fixed coefficients with an invertible A₀, μ is an n × 1 vector of fixed coefficients, and ε_t represents structural economic shocks with an expected value zero and a covariance matrix I_n. i is the number of lags, which, following standard practice in models with quarterly data, is set to four (i = 4). 

The SVAR model is used to compute the impulse response functions (IRFs):

(A2)

where ψ_jk,h represents the median response of variable j to shock k after h periods. 

In order to assess the relative importance of individual shocks (in absolute terms) in determining the dynamics of wages, or the historical decomposition of wages, which is necessary for calculating the time-varying correlation between wages and prices, we use the formula proposed by Deskar-Škrbić, Kotarac and Kunovac (2020):

(A3)

In (A3), the contribution of shock k to variable j in period t, can be calculated as:

(A4)

Unless otherwise specified in the results, we report the median and the 16^th and 84^th percentiles of the distribution of impulse responses over a horizon ranging from 1 to 12 or 24 quarters.

Following the approach of Deskar-Škrbić, Kotarac and Kunovac (2020), we apply the Gibbs sampling algorithm using the Independent Normal Inverse Wishart prior. At each step of the Gibbs sampler, with a given sample of VAR model parameters in reduced form, we derive a set of structural models that satisfy the sign and zero restrictions used to identify the shocks. For the VAR model parameters to which no restrictions are applied, we use standard Minnesota priors, setting λ₁ = 0.₂, λ2 = 0.5, λ₃ = 2, and λ₄ = 10000. This choice reflects the use of a tight prior, in contrast to Deskar-Škrbić, Kotarac and Kunovac (2020), who employ loose priors.

Data

Table A1

Data and data sources, 2004-2023

DISPLAY Table

Public sector services harmonized consumer price index calculation 

The public sector services HICP is calculated by multiplying the share of spending on a specific product by activity (CPA) in the public sector, which is linked to the corresponding consumption category by purpose (COICOP) in the matrices from Cai and Vandyck (2020), with the relevant HICP index for that consumption purpose category. The columns of the matrices in Cai and Vandyck (2020) consist of the second-level hierarchical classification of products by activity, which can easily be mapped to the corresponding activities defined by the EU’s statistical classification of economic activities (NACE). The rows in these tables represent consumption categories according to the COICOP classification at the second level (divisions). Each table cell contains data on spending for a specific COICOP category associated with a corresponding CPA product category. To calculate inflation for a given sector, the share of consumption allocated to that sector within the total consumption of a specific category is multiplied by the corresponding second-level HICP sub-index. A sample calculation for the health services sector (Q86) and the resulting HICP for health services is presented in table A2 and graph A1. In this case, the relevant COICOP consumption categories for the human health services are CP062 (out-patient services) and CP063 (hospital services). For each category, the share of total consumption is calculated, which is then multiplied by the HICP for outpatient and hospital services, and subsequently rescaled so that the index for the base year equals 100.

Table A2

Part of the bridging matrices related to the human health services

DISPLAY Table

Graph A1

HICP for human health services and associated subcomponents

DISPLAY Graph

Impulse response functions in the public sector model

Graph A2

Impulse response functions

DISPLAY Graph

Impulse response functions in the overall economy model 

Graph A3

Impulse response functions

DISPLAY Graph

Results from the model of the overall economy using gross value added and the unemployment rate 

Graph A4

Impulse response functions

DISPLAY Graph

Graph A5

Shock dependent wage-to-price multipliers

DISPLAY Graph

Graph A6

Cumulative response of public sector prices to a one-standard-deviation wage mark-up shock

DISPLAY Graph

Graph A7

Estimated potential effect of public sector wage growth on headline inflation in 2024 (pp)

DISPLAY Graph

Results from the model of the overall economy using gross domestic product and the unemployment rate 

Graph A8

Impulse response functions

DISPLAY Graph

Graph A9

Shock dependent wage-to-price multipliers

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Graph A10

Cumulative response of public sector prices to a one-standard-deviation wage mark-up shock

DISPLAY Graph

Graph A11

Estimated potential effect of public sector wage growth on headline inflation in 2024 (pp)

DISPLAY Graph

Results from the model of the overall economy using gross domestic product and employment 

Graph A12

Impulse response functions

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Graph A13

Shock-dependent wage-to-price multipliers

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Graph A14

Cumulative response of public sector prices to a one-standard-deviation wage mark-up shock

DISPLAY Graph

Graph A15

Estimated potential effect of public sector wage growth on headline inflation in 2024 (pp)

DISPLAY Graph

Results from the model of the overall economy using gross value added and employment estimated before the COVID-19 pandemic (2004Q1-2019Q4) 

Graph A16

Graph A16 Impulse response functions

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Graph A17

Shock-dependent wage-to-price multipliers

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Graph A18

Cumulative response of public sector prices to a one-standard-deviation wage mark-up shock

DISPLAY Graph

Graph A19

Estimated potential effect of public sector wage growth on headline inflation in 2024 (pp)

DISPLAY Graph

Results from the model of the overall economy using gross domestic product and unemployment rate estimated before the COVID-19 pandemic (2004Q1-2019Q4) 

Graph A20

Impulse response functions

DISPLAY Graph

Graph A21

Shock-dependent wage-to-price multipliers

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Graph A22

Cumulative response of public sector prices to a one-standard-deviation wage mark-up shock

DISPLAY Graph

Graph A23

Estimated potential effect of public sector wage growth on headline inflation in 2024 (pp)

DISPLAY Graph

Historical decomposition of nominal wages 

Graph A24

Historical decomposition of nominal wages

DISPLAY Graph

Notes

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2024

2024

* The author would like to thank two anonymous reviewers for their valuable comments, suggestions, and insights, which contributed to shaping this paper. Special thanks to Davor Kunovac for his ideas behind the methodology for calculating the effects of total wage growth on inflation, which served as the foundation for the approach used in this paper to estimate the impact of public sector wage growth on overall inflation. Additionally, the author acknowledges the use of ChatGPT (version 4.0 mini) to enhance the translation, readability, and overall language quality of the paper. The views and opinions expressed in this article are those of the author and do not necessarily reflect the official policy or position of the Croatian National Bank.

**The article was judged the best regular article in the 2024 annual competition of the Hanžeković Foundation.

¹ For instance Index argued that in 2022 labour costs (nominal wages) were increasing but that simultaneously real wages were decreasing (see Perković, 2022). From the context of the argumentation it is clearly implied that substantial nominal wage growth at the time (7.5% yearly) was not enough to offset inflation, the suggestion being that more nominal wage growth is required.

² During the periods of elevated inflation, particularly in the first half of 2023, concerns arose about the potential for a wage-price spiral. For instance, the Croatian Employers’ Association cautioned that robust wage growth “raises the risk of a wage and retail price spiral” (---, 2024). This risk was taken seriously amid strong price increases, as reflected in remarks by key central bank figures. Notably, ECB President Christine Lagarde addressed the issue in a 2023 speech (ECB, ref13615#2023), and CNB Governor Boris Vujčić noted in 2024 that inflationary pressures had been contained before a wage-price spiral could take hold (CNB, 2024a).

³ For instance in Lider (---, 2024b) and HRT (see: Kovaček, 2024).

⁴ Which includes public administration and defence services; compulsory social security services (O), education services (P), and human health services (Q).

⁵ See Deutsche Bundesbank (2019). It is important to note that consumers (and central banks) are primarily interested in the potential pass-through of wage growth to consumer prices measured by the Harmonized Index of Consumer Prices (HICP). In contrast, the conclusions of theoretical models generally refer to prices measured by the GDP deflator, which captures the prices of goods produced within the domestic economy. Since consumers also purchase imported goods and since a significant share of imported intermediates is used in the domestic production of consumer goods, the pass-through of wage growth to consumer prices will not necessarily correspond to the pass-through of wage growth to the prices of goods produced within the domestic economy.

⁶ Markets are often not perfectly competitive, allowing companies to set prices above marginal costs, meaning they can charge markups. These markups do not necessarily remain constant, so companies can adjust them to mitigate (or amplify) the pass-through of higher wages to prices by reducing (or increasing) their markups. 7 In describing the model, we abstract from the effect of so-called aspiration wages, which Blanchard and Bernanke (2023) consider in their highly influential paper. Specifically, while standard WS-PS models typically do not include aspiration wages (see, for example, Carlin and Soskice, 2014), integrating the concept of aspiration wages explicitly into the methodological approach underlying the empirical estimation would be challenging.

⁷ In describing the model, we abstract from the effect of so-called aspiration wages, which Blanchard and Bernanke (2023) consider in their highly influential paper. Specifically, while standard WS-PS models typically do not include aspiration wages (see, for example, Carlin and Soskice, 2014), integrating the concept of aspiration wages explicitly into the methodological approach underlying the empirical estimation would be challenging.

⁸ In the empirical model, expectations are not explicitly modelled because the time series of short-term and long-term inflation expectations published by Consensus Economics for Croatia is too short and only available at a semi-annual frequency.

⁹ For instance, Gumiel and Elke (2018), Bobeica, Ciccarelli and Vansteenkiste (2019, 2021).

¹⁰ The potential output is assumed to be the level of income achieved at the natural rate of unemployment, that is, the unemployment rate that does not accelerate inflation (Non-Accelerating Inflation Rate of Unemployment, NAIRU).

¹¹ The idea that the pass-through of wages to prices can vary depending on the shocks affecting an economy originates from the literature on exchange rate pass-through to inflation, as discussed in the papers of Kunovac and Communale (2017), and Forbes, Hjortsoe and Nenova (2018).

¹² The authors adopt the idea of identifying the effects of specific shocks using a hypothetical scenario from the literature related to isolating the role of confidence in the transmission of government spending shocks (Bachmann and Sims, 2012) and isolating the role of the credit channel in the transmission of monetary shocks (Ciccarelli, Maddaloni and Peydró, 2015).

¹³ The identification scheme relies on sign restrictions on impulse response functions proposed by Canova and De Nicolò (2022), and Uhlig (2005), and further refined by Rubio-Ramírez, Waggoner and Zha (2010), and Arias, Rubio- Ramirez and Waggoner (2014).

¹⁴ Data, data sources and their modifications are available in table A1.

¹⁵ According to the statistical classification of products by activity (CPA) section O includes public administration and defence services; compulsory social security services, section P includes education services, and section Q includes human health and social work services.

¹⁶ Harmonised index of consumer prices.

¹⁷ The HICP for public sector services is calculated as the share of consumption of a specific product by activity (CPA) in the public sector which is linked in the conversion tables to the corresponding category of consumption by purpose (COICOP) and the corresponding HICP index by purpose of consumption (COICOP). See explanation for table A2 and graph A1 for details.

¹⁸ Calculated using Croatian Bureau of Statistics (CBS) data collected through regular monthly surveys on net and gross wages according to the classification of economic activities in the European community (NACE).

¹⁹ Calculated as the ratio of GVA (gross value added of the O-Q sections) and the number of employees (in the O-Q sections).

²⁰ The correlation coefficient is 0.56.

²¹ For example, structural reforms that lead to changes in wages regardless of the prevailing economic conditions (such as the 2024 public sector reform) or alter workers’ bargaining power serve as good examples.

²² It is important to note that this approach to analysing the effects of wages on inflation differs from cases where wage changes are the result of endogenous wage reactions to various economic shocks. In those situations, it is necessary to isolate the labour cost channel to evaluate its contribution to inflation at a specific point in time, considering the mix of shocks affecting the economy at that moment. It that case the focus is on the role of wages in amplifying the effects of economic shocks on inflation. The concept of studying “amplification” in a VAR model by constructing a hypothetical scenario – where wages do not respond to a specific shock – was employed by Ivanac, Kunovac and Nadoveza (2024), drawing on the methodology of Bachmann and Sims (2012) and Ciccarelli, Maddaloni and Peydró (2015).

²³ The price response is measured by the impulse response function (IRF) of the public sector services HICP to a one-standard-deviation wage mark-up shock over a given horizon, h.

²⁴ In the case of wage spillover effects, the indirect effect can be calculated by using the impulse response function of inflation to wage mark-up shock and the estimated economy-wide wage mark-up shock.

²⁵ I.e., the relationship between wages and prices under different shocks, or the conditional correlations between wage growth and inflation.

²⁶ As explained in the theoretical section, wages are endogenous and primarily driven by inflation in previous periods (wages catch-up to maintain real purchasing power) and labour productivity (if wage growth is offset by productivity gains it does not create additional production costs). To calculate the wage shock, the wage increase related to reform must be adjusted to account for last year’s inflation and the anticipated labour productivity growth in the public sector. The expected annual productivity growth rate is 0.65%, which reflects the average of the annual growth rates derived from the Hodrick-Prescott trend of public sector labour productivity, based on the ratio of gross value added to employment in the O-Q sector.

²⁷ See: Government of RC (2024).

²⁸

²⁹ See: Government of RC (2024).

³⁰ 

³¹  

³² Although it may appear counterintuitive, it’s important to note that any cost shock, by definition, negatively impacts production and leads to a reduction in employment (or an increase in unemployment). As a result, the pass-through of higher corporate wage bill to prices is moderated by the negative effects of reduced production and lower employment. In contrast, during demand shocks, the increase in costs due to wage growth further exacerbates price increases driven by strong demand.

Disclosure statement

References

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2. ---, 2024b. Rekordno povećanje mase plaća i neto plaća u javnom sektoru nije vezano uz reformu uprave. Lidermedia, June 22. 


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15. Ciccarelli, M., Maddaloni, A. and Peydró, J. L., 2015. Trusting the Bankers: A New Look at the Credit Channel of Monetary Policy. Review of Economic Dynamics, 18(4), pp. 979-1002 [CrossRef]


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37. Rubio-Ramírez, J. F., Waggoner, D. F. and Zha, T., 2010. Structural Vector Autoregressions: Theory of Identification and Algorithms for Inference. The Review of Economic Studies, 77(2), pp. 665-696 [CrossRef]


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41. Whiteley, P., 2023. Does Public Sector Pay Drive Inflation? LSE Blogs, February 21.

---, 2024a. HUP: Snažan realni rast plaća usporava pad inflacije. Lidermedia, April 6. 

---, 2024b. Rekordno povećanje mase plaća i neto plaća u javnom sektoru nije vezano uz reformu uprave. Lidermedia, June 22. 

Arce, Ó. [et al.], 2024. What caused the euro area post-pandemic inflation? ECB Occasional Paper, No. 343 [CrossRef]

Arias, J. E., Rubio‐Ramírez, J. F. and Waggoner, D. F., 2014. Inference Based on SVAR Identified with Sign and Zero Restrictions: Theory and Applications. International Finance Discussion Papers, No. 1100 [CrossRef]

Bachmann, R. and Sims, E. R., 2012. Confidence and the Transmission of Government Spending Shocks. Journal of Monetary Economics, 59(3), pp. 235-249 [CrossRef]

Bidder, R. M., 2015. Are Wages Useful in Forecasting Price Inflation? FRBSF Economic Letter, No. 2015-33. 

Blanchard, O. J. and Bernanke, B. S., 2023. What Caused the US Pandemic-Era Inflation? NBER Working Paper, No. 31417 [CrossRef]

Blanchard, O. J., 1986. The Wage Price Spiral. The Quarterly Journal of Economics, 101(3), pp. 543-565 [CrossRef]

Bobeica, E., Ciccarelli, M. and Vansteenkiste, I., 2019. The Link Between Labour Cost and Price Inflation in the Euro Area. ECB Working Paper, No. 2235 [CrossRef]

Bobeica, E., Ciccarelli, M. and Vansteenkiste, I., 2021. The Changing Link Between Labour Cost and Price Inflation in the United States. ECB Working Paper, No. 2583. 

Cai, M. and Vandyck, T., 2020. Bridging Between Economy-Wide Activity and Household-Level Consumption Data: Matrices for European Countries. Data in Brief, 30(June), 105395 [CrossRef]

Canova, F. and De Nicolo, G., 2002. Monetary Disturbances Matter for Business Fluctuations in the G-7. Journal of Monetary Economics, 49(6), pp. 1131-1159 [CrossRef]

Carlin, W. and Soskice, D., 2014. Macroeconomics: Institutions, Instability, and the Financial System. Oxford: Oxford University Press.

Chang, C. P. and Emery, K. M., 1996. Do Wages Help Predict Inflation? Economic and Financial Policy Review, Federal Reserve Bank of Dallas, Q I, pp. 2-9.

Ciccarelli, M., Maddaloni, A. and Peydró, J. L., 2015. Trusting the Bankers: A New Look at the Credit Channel of Monetary Policy. Review of Economic Dynamics, 18(4), pp. 979-1002 [CrossRef]

CNB, 2024a. Inflacijski val je zauzdan prije nego što se uspjela aktivirati spirala cijena i plaća. Croatian National Bank, May 21.

CNB, 2024b. Makroekonomska kretanja i prognoze, 9(6). Zagreb: Croatian National Bank.

Conti, A. M. and Nobili, A., 2019. Wages and Prices in the Euro Area: Exploring the Nexus. Questioni di Economia e Finanza (Occasional Papers), No. 518. 

Dedola, L. and Neri, S., 2007. What Does a Technology Shock Do? A VAR Analysis with Model-Based Sign Restrictions. Journal of Monetary Economics, 54(2), pp. 512-549 [CrossRef]

Deskar-Škrbić, M., Kotarac, K. and Kunovac, D., 2020. The Third Round of the Euro Area Enlargement: Are the Candidates Ready? Journal of International Money and Finance, 107, 102205 [CrossRef]

Deutsche Bundesbank, 2019. The Impact of Wages on Prices in Germany: Evidence from Selected Empirical Analyses. Deutsche Bundesbank Monthly Report, September, pp. 15-37. 

ECB, 2023. Speech by Christine Lagarde, President of the ECB, at the ECB Forum on Central Banking 2023 on “Macroeconomic stabilisation in a volatile inflation environment” in Sintra, Portugal. 

Forbes, K., Hjortsoe, I. and Nenova, T., 2018. The Shocks Matter: Improving Our Estimates of Exchange Rate Pass-Through. Journal of International Economics, 114(C), pp. 255-275 [CrossRef]

Foroni, C., Furlanetto, F. and Lepetit, A., 2018. Labour Supply Factors and Economic Fluctuations. International Economic Review, 59(3), pp. 1491-1510 [CrossRef]

Galí, J. and Gambetti, L., 2019. Has the U.S. Wage Phillips Curve Flattened? A Semi-Structural Exploration. NBER Working Paper, No. 25476 [CrossRef]

Government of Republic of Croatia, 2024. Osnovni koeficijenti zaposlenih u državnoj službi, Hrvatskoj vojsci i javnim službama. 

Gumiel, J. and Hahn, E., 2018. The Role of Wages in the Pickup of Inflation. Economic Bulletin Boxes, 5(4).

Hahn, E., 2020. The Wage-Price Pass-Through in the Euro Area: Does the Growth Regime Matter? ECB Working Paper, No. 2485 [CrossRef]

Hu, L. and Toussaint-Comeau, M., 2010. Do Labour Market Activities Help Predict Inflation? Economic Perspectives, 34(2), pp. 52-63.

Ivanac, F., Kunovac, D. and Nadoveza, O., 2024. Kako porast plaća utječe na inflaciju. HNBlog, August 29.

Jarocinski, M. and Mackowiak, B., 2017. Granger Causal Priority and Choice of Variables in Vector Autoregressions. The Review of Economics and Statistics, 99(2), pp. 319-329 [CrossRef]

Knotek, E. S. and Zaman, S., 2014. On the Relationships Between Wages, Prices, and Economic Activity. Economic Commentary, No. 2014-14 [CrossRef]

Kovaček, D., 2024. Može li rast plaća utjecati na stopu inflacije? HRT, March 2.

Kunovac, D. and Comunale, M., 2017. Exchange Rate Pass-Through in the Euro Area. CNB Working Paper, W-46.

Peersman, G. and Straub, R., 2009. Technology Shocks and Robust Sign Restrictions in a Euro Area SVAR. International Economic Review, 50(3), pp. 727-750 [CrossRef]

Perković, B., 2024. Realne plaće padaju, a troškovi rada rastu. Stvara se katastrofalna situacija. Index.hr, October 3. 

Rubio-Ramírez, J. F., Waggoner, D. F. and Zha, T., 2010. Structural Vector Autoregressions: Theory of Identification and Algorithms for Inference. The Review of Economic Studies, 77(2), pp. 665-696 [CrossRef]

Stock, J. H. and Watson, M. W., 2008. Phillips Curve Inflation Forecasts. NBER Working Paper, No. 14322 [CrossRef]

Tatierska, S., 2010. Do Unit Labour Costs Drive Inflation in the Euro Area? Bank of Slovakia Working Paper, WP 2/2010.

Uhlig, H., 2005. What Are the Effects of Monetary Policy on Output? Results from an Agnostic Identification Procedure. Journal of Monetary Economics, 52(2), pp. 381-419 [CrossRef]

Whiteley, P., 2023. Does Public Sector Pay Drive Inflation? LSE Blogs, February 21.