Corporate Concentration and Labour Conditions in Hungary’s Food Industry: Evidence on Wages, Bonuses, Working Time, and Workers’ Rights (1993–2022)

Abstract

This study examines the relationship between corporate concentration and labour market conditions in Hungary’s food industry over the period 1993–2022. Using industry-level panel data for the four most highly concentrated subsectors, cereals, food processing, oils and fats, and sugar and confectionery, corporate concentration is measured using the Herfindahl–Hirschman Index (HHI), and a two-way fixed-effects panel regression model is employed to assess its association with wage structures, working-time arrangements, and employment composition. The results reveal a statistically significant negative relationship between corporate concentration and both gross monthly earnings and base hourly wages. A 1000-point increase in the HHI is associated with an approximately 10 percent decline in base wages. Higher concentration is also positively associated with greater reliance on part-time employment and increased overtime intensity, alongside a significant reduction in paid leave provision. Importantly, when variables capturing working-time arrangements and employment structure are incorporated into the earnings model, the direct effect of concentration becomes statistically insignificant. This pattern likely reflects the fact that these variables are directly embedded in the determination of gross monthly earnings, suggesting that the effect of concentration operates indirectly through adjustments in working time and employment composition rather than through a purely independent channel. This finding suggests that the impact of concentration on wages operates partly through structural adjustments in compensation systems and increased labour flexibility. Overall, the evidence indicates that corporate concentration in Hungary’s food manufacturing sector does not necessarily reduce nominal earnings but instead reshapes their composition. The role of base wages weakens, while regular bonuses emerge as the primary mechanism of income adjustment, increasing managerial discretion and income volatility. These findings contribute to the literature on labour market monopsony in transition economies and underscore the importance of integrating labour market considerations into competition policy frameworks.

1. Introduction

1.1. Big Picture

A market structure known as “corporate concentration” occurs when a small number of companies control labour, capital, and technology to dominate an upstream market (Striffler, 2024). By controlling essential inputs and the initial phases of the supply chain, these businesses are able to increase profitability through the exercise of market dominance and the ability to suppress input prices, particularly wages, below competitive levels (Passerini, 2025). Corporate concentration, which is frequently justified by efficiency gains, higher profit margins, increased market share, enhanced corporate concentration, and digitalization, causes structural changes in markets and industries (Oleš, 2024). However, its effects on labour markets and employment conditions have caused policymakers, labour-oriented civil society organizations, and researchers to become increasingly concerned. The scholarly literature highlights how workers’ bargaining power is weakened, labour’s share of value added is decreased, job quality declines, and labour market inequality and discrimination are exacerbated by excessive corporate concentration and the various forms of power granted to dominant firms (Clapp et al., 2025). In addition to price channels and product market competition (Williams, 2022), corporate concentration in product markets also affects wages, compensation structures, work intensity, and non-wage employment conditions by creating monopsony or quasi-monopsony power in labour markets (Palladino, 2019). In these circumstances, leading firms can reduce real wages, bonuses, working hours, and employment benefits more effectively without losing employees (Clapp, 2022). These dynamics are especially noticeable in industries with high barriers to entry, particularly in countries where labour market institutions have undergone reforms toward reduced regulation and weaker protections for workers. These nations were previously known for having more closed, centrally planned economic structures, but since the 1990s, they have been exposed to more foreign direct investment (FDI). The necessity for a more thorough empirical investigation of the connection between corporate concentration and working conditions is highlighted by this context (Diprima, 2023; Špička, 2016).

Hungary presents a particularly relevant institutional context for studying the labour market effects of corporate concentration. As a post-socialist transition economy, it has experienced significant structural changes since the early 1990s, including extensive privatization, large inflows of foreign direct investment (FDI), and a comprehensive restructuring of industrial ownership patterns (Van Zuilekom & Morrison, 2013). Alongside these changes, wage-setting procedures have become more decentralized, union density has decreased, and collective bargaining organizations have been weaker. As a result, Hungary’s labour market results are influenced by a special mix of integration into global value chains and emerging market institutions (Diprima, 2023).

Since the early 1990s, Hungary’s labour market has undergone significant regulatory changes following the transition from a centrally planned to a market-based economy. During this period, union density declined, collective bargaining mechanisms weakened, and labour market institutions became increasingly decentralized. This shift has increased employer discretion over compensation structures, including bonuses and supplementary payments (Csaba, 2022). At the same time, working-time regulations have been shaped by both domestic reforms and European Union directives, particularly following Hungary’s accession to the EU in 2004. While statutory frameworks governing working hours, overtime, and paid leave have been maintained, their implementation has allowed for considerable flexibility at the firm level. These institutional developments have contributed to increasing heterogeneity in working conditions and earnings composition over time, providing an important context for interpreting the empirical findings of this study (Daskalova, 2020).

In this context, corporate concentration may have stronger implications for labour market outcomes compared to more regulated Western European economies.

1.2. Literature Gap

While existing research has examined the relationship between corporate concentration and labour market outcomes, much of this work has focused primarily on wage levels (Izumi et al., 2023) and employment outcomes (Rinz, 2022). As a result, important dimensions of working conditions remain underexplored. In particular, working-time arrangements such as overtime and paid leave, as well as the employment conditions of part-time and non-permanent workers, have received considerably less attention. Moreover, compensation structures beyond base wages, including regular and irregular bonuses, allowances, and other non-wage benefits, are often treated as secondary, despite their growing importance in shaping overall earnings (Passerini, 2025; Zhang & Wang, 2025).

Furthermore, the empirical evidence that is currently available is mainly limited to developed economies, specifically Western European nations (Daskalova, 2020; Izumi et al., 2023; Oleš, 2024), Canada (Clapp, 2021, 2022), and the United States (Carey & Nasir, 2019; Kristal, 2013; LeBaron, 2020). In contrast, Central and Eastern European transition economies display distinct labour market institutions and collective bargaining mechanisms. These economies were centrally planned before 1990 and have since experienced significant structural changes (Csaba, 2022), including widespread privatization (Van Zuilekom & Morrison, 2013), rising foreign direct investment (András, 2014; Diprima, 2023), and increasing corporate concentration, particularly driven by Western investors (Čechura et al., 2015; Špička, 2016).

The food industry, which is well known in the literature for its strong buyer power, rising merger activity and supply chain concentration, and high capital intensity (Clapp, 2021; Striffler, 2024), has a particularly noticeable research gap. The food industry is considered a strategic sector for employment and economic development in Hungary, where it generates about one-third of the country’s total revenue (Imani Bashokoh et al., 2025). However, there are still few comprehensive empirical studies that examine the relationship between corporate concentration and multiple dimensions of working conditions within a unified analytical framework over an extended period of time. Previous research has mostly concentrated on specific subsectors of the Hungarian food industry, covering brief time periods and a small range of labour-related factors (Deconinck, 2021; Kurmai, 2016; Nes et al., 2021; Réger & Horváth, 2020; Perekhozhuk et al., 2013). In order to close this gap, this study examines how corporate concentration affects non-contractual and part-time employees’ wages, bonuses, working hours, non-wage benefits, and working conditions in the Hungarian food industry between 1993 and 2022. While the empirical analysis begins in 1993 due to data availability, it is important to note that prior to 1990, Hungary’s food industry operated within a centrally planned economic system characterized by state ownership and administratively determined production structures. In this context, conventional measures of corporate concentration, such as the HHI, are not directly comparable to post-transition market conditions. The period following the early 1990s therefore represents the emergence of market-based competition, privatization, and restructuring, making it a relevant starting point for the analysis.

1.3. Research Contribution

This study makes several significant contributions to the existing literature on corporate concentration and working conditions. First, it offers new empirical evidence on the connection between labour market outcomes and corporate concentration in Hungary, a Central and Eastern European transition economy with a specific focus on the food sector, which serves as an illustrative case for analysing these dynamics in a transition economy context. The analysis uses a long-term dataset from 1993 to 2022 to capture structural changes brought about by widespread privatization, increased foreign direct investment, and growing corporate concentration over time.

In this research, corporate concentration refers to product market concentration measured using the Herfindahl–Hirschman Index (HHI). While labour market concentration is not directly measured, product market concentration may translate into labour market power through monopsonistic mechanisms.

In this context, the analysis focuses on four of the nine major subsectors of the Hungarian food industry, cereals and cereal products, food processing, oils and fats, and sugar and confectionery, selected due to their relatively high levels of corporate concentration compared to other subsectors.

Second, by examining a broad range of labour market outcomes, the study extends the existing literature beyond its predominant focus on wages and employment levels. However, the analysis is based on subsectors with relatively high levels of corporate concentration, and the results should therefore be interpreted within this context, as patterns may differ in less concentrated subsectors. These consist of regular and irregular bonuses and allowances, non-wage benefits, working-time arrangements, and the incidence of part-time employment. A more thorough evaluation of the impact of corporate concentration on labour’s share of value added and job quality is made possible by this multifaceted approach. Finally, the study emphasizes how corporate concentration affects labour market working conditions in addition to product market outcomes. The paper provides policy-relevant insights for discussions on labour market regulation and competition policy in transition economies like Hungary by outlining how dominant firms can exert more control over pay structures and employment conditions.

1.4. Research Questions

• From 1993 to 2022, how has corporate concentration changed in Hungary’s food industry?
• How is corporate concentration associated with wage-related outcomes, including base wages and regular and non-regular bonuses?
• What effects does corporate concentration have on non-wage working conditions, such as working-time arrangements, paid leave, and fringe benefits?
• Does the prevalence of non-standard work arrangements and part-time employment change as corporate concentration rises?

1.5. Research Approach

Using industry-level data from the Hungarian food sector covering the period 1993–2022, this study employs a long-term empirical approach to address its research questions. The analysis focuses on four subsectors with the highest levels of corporate concentration. Using a multidimensional set of indicators capturing both worker characteristics and job-related conditions, the study examines how changes in corporate concentration are associated with wages, bonuses, working-time arrangements, non-wage benefits, and employment structures over time.

2. Literature Review

2.1. Corporate Concentration and Wage Level and Earnings

The initial investigations into corporate concentration and its economic implications stem from the structure conduct performance (SCP) paradigm established in industrial organization. This framework stressed how the structure of the market, especially how concentrated it is, affects how businesses act and the economy as a whole. In this situation, higher levels of concentration were linked to more market power, which let companies change prices, output decisions, and maybe even how wages are set (Williams, 2022).

Later work in labour economics and industrial organization improved this view by introducing the idea of monopsony power. Recent research indicates that employer concentration can diminish workers’ bargaining power and result in wage suppression, even in the absence of conventional product market monopolies power (Izumi et al., 2023; Rinz, 2022).

Corporate concentration refers to a market structure in which a limited number of dominant firms command a substantial share of market output, technology, revenue, capital, and labour (Imani Bashokoh & Korani, 2024). Such a structure reduces market dynamism and weakens competitive pressures, thereby discouraging entry by smaller or younger firms and enhancing incumbents’ pricing power (Mumbower & Garrow, 2010; Rahman et al., 2016; Wood, 2013).

While managers and owners of dominant firms often justify concentration by invoking efficiency gains, economies of scale, and productivity improvements, the implications of increased corporate concentration extend beyond product markets and deeply affect labour market outcomes (Fernández-Villaverde et al., 2021). In particular, product corporate concentration tends to be mirrored by labour market concentration, enabling firms to exercise monopsony power (Fernández-Villaverde et al., 2021; Schiavone, 2023).

According to monopsony theory, when a limited number of firms dominate labour demand within a given industry or geographic area, employers can set wages below workers’ marginal productivity without triggering substantial labour outflows (Berger et al., 2022). Reduced competition among employers weakens outside options for workers, especially when smaller firms exit the market or become subsidiaries of larger corporate groups (Brennan, 2016). As a result, workers’ bargaining power declines, and wage-setting becomes increasingly employer-driven.

Empirical evidence consistently supports this theoretical framework. A growing body of research finds that higher levels of corporate concentration are associated with slower wage growth, independent of price inflation, and with a declining labour share of value added (Bakir et al., 2021; Izumi et al., 2023; Sharma & Rotthoff, 2019). These effects are particularly pronounced in industries characterized by vertical integration, high capital intensity, and limited labour mobility (T. Liu et al., 2025), where switching costs and skill specificity further constrain workers’ outside options. Importantly, corporate concentration influences not only wage levels but also the structure and composition of compensation. In concentrated markets, stable and institutionalized components of pay such as base wages and regular bonuses governed by formal agreements are more likely to be restrained. Dominant firms possess greater leverage to shape formal wage-setting frameworks and collective agreements in ways aligned with their strategic and profitability objectives (Kristal, 2013; Schiavone, 2023). Consequently, increases in corporate concentration are often associated with the standardization, reduction, or restructuring of regular bonuses.

Simultaneously, compensation systems in concentrated environments increasingly rely on performance-based pay and discretionary bonuses (Nisar, 2007; Sheikh et al., 2018; Yoshikawa et al., 2010). These variable components are frequently positioned outside collective bargaining frameworks and are subject to limited oversight by labour representatives, allowing firms to adjust them flexibly in response to financial performance and strategic priorities (Freitas et al., 2020; Zulfiqar & Hussain, 2020). Although nominal base wages may remain fixed, this shift toward variable compensation increases income volatility and effectively transfers greater economic risk from firms to workers.

Nevertheless, the magnitude and form of labour market adjustments associated with corporate concentration depend on institutional labour market conditions, including not only wage dynamics but also broader mechanisms of risk transfer and shifts in the balance of power between firms and workers. Factors such as collective bargaining coverage, labour mobility, ownership structure, and minimum wage regulations can moderate the relationship between concentration and employer power (Izumi et al., 2023; Rinz, 2022). In labour markets characterized by strong collective institutions and regulatory protections, the adverse effects of concentration on workers including wage outcomes as well as broader aspects of working conditions and employment security tend to be attenuated (Clapp, 2024; Clapp et al., 2025). Conversely, in environments with weak bargaining institutions and high labour market frictions, dominant firms are better positioned to redesign compensation systems, contractual arrangements, and wage-setting mechanisms to their advantage (Bakir et al., 2021).

Overall, the literature indicates that rising corporate concentration reshapes not only wage levels but also the stability and composition of income. By strengthening monopsony power, dominant firms can strategically manage both fixed and variable components of compensation, suppress base wages, restructure regular bonuses, and expand discretionary performance-based payments. These dynamics suggest that the consequences of concentration extend beyond price-setting behaviour in product markets and fundamentally transform labour market outcomes. Based on these theoretical considerations, the following hypotheses are proposed:

H1a. 

Higher corporate concentration is associated with lower hourly base wages.

H1b. 

Higher corporate concentration is associated with lower regular bonuses.

H1c. 

Higher corporate concentration is associated with greater share of non-regular bonuses in total earnings.

H1d. 

Higher corporate concentration is associated with lower gross monthly earnings.

To examine the time dynamics of corporate concentration, the following trend specification is estimated:

$$HH{I}_{it}=\alpha +\delta Tren{d}_t+{\mu }_i+{\epsilon }_{it}$$

where ${\epsilon }_{it}$ is the idiosyncratic error term, assumed to have zero mean and constant variance. Standard errors are clustered at the subsector level to account for potential heteroskedasticity and serial correlation within subsectors over time.

Where:

• $HH{I}_{it}$ represents the Herfindahl–Hirschman Index in subsector i at time t,
• $Tren{d}_t$ captures the linear time trend,
• ${\mu }_i$ denotes subsector fixed effects,
• The coefficient $\delta$ captures the direction and magnitude of the time trend in concentration,
• $i$ denotes the subsector-level unit of analysis. In this study, “subsector” refers to the four major segments of the Hungarian food manufacturing industry selected for analysis (cereals and cereal products, food processing, oils and fats, and sugar and confectionery). The empirical analysis is conducted at this aggregated subsector level, although each subsector may include further internal divisions.

Empirical specification:

$$\mathrm{l}\mathrm{n}\left(Wag{e}_{it}\right)={\beta }_{1}HH{I}_{it}+{\mu }_i+{\lambda }_t+u_{it}$$

where:

• ${Wage}_{it}$ represents either base hourly wages or gross monthly earnings in subsector $i$ at time $t$, depending on the specification,
• ${\mu }_i$ are subsector fixed effects,
• ${\lambda }_t$ are year fixed effects,
• $u_{it}$ is the idiosyncratic error term associated with the wage equation, assumed to satisfy standard conditions. Standard errors are clustered at the subsector level.

Expected sign:

$${\beta }_1<0$$

2.2. Corporate Concentration and Work Intensity and Flexibility

This study further examines how corporate concentration shapes working conditions and the organization of work. In industries characterized by high levels of concentration, dominant firms face fewer competitive constraints in managing labour and structuring production processes. As corporate concentration increases, these firms gain greater discretion over work scheduling, task allocation, and workforce organization, enabling them to adjust labour inputs in ways that primarily serve firm-level efficiency and profitability objectives (Chinetti, 2025; Passerini, 2025).

One important indicator of labour market insecurity is the share of part-time employment. The literature suggests that in concentrated markets, firms face weaker competitive and institutional pressures to provide stable, full-time employment arrangements. Consequently, they are more likely to expand non-standard forms of employment, including part-time, temporary, and other flexible contracts (Benton & Kim, 2022; X. Liu et al., 2025).

The increasing reliance on part-time and other atypical contracts enables large firms to reduce labour-related costs, particularly those associated with social protection obligations such as pensions, insurance, and other employment benefits. Empirical evidence indicates that these strategies are especially prevalent in sectors characterized by high capital intensity, significant sunk investments, and vertical integration (T. Liu et al., 2025). In such environments, workers’ outside employment options are limited, making the acceptance of less secure employment arrangements more likely and transforming contractual flexibility into a managerial instrument of cost control. In a concentrated market, this pattern represents a structural redistribution of employment risk and bargaining power from corporations to workers, in addition to cost efficiency concerns.

Beyond employment status, work intensity constitutes another critical dimension of labour market outcomes. Indicators such as overtime hours provide insight into the degree of work pressure and labour utilization. Firms with greater corporate concentration are more likely to increase the workload of existing employees through multitasking, job enlargement, or additional training rather than hiring and training new workers (Begall & van der Lippe, 2020; Tuckman, 2005).

Such strategies allow firms to avoid recruitment and training costs while limiting long-term obligations related to social security contributions and employee benefits, all while maintaining or increasing productivity levels. In monopsonistic labour markets, workers possess limited bargaining power to resist excessive workloads, compressed schedules, or unfavourable work arrangements (Brennan, 2016; T. Liu et al., 2025). Consequently, rising overtime hours may reflect not only productivity considerations but also asymmetric power relations between employers and employees.

Overall, the literature suggests that corporate concentration reshapes workplace structures by expanding the use of non-standard employment arrangements and intensifying work pressure. This pattern is also reflected in broader labour market developments in Hungary over the post-transition period. Descriptive evidence indicates a gradual increase in non-standard forms of employment, including part-time and temporary work, alongside changes in working-time arrangements and job stability. Compared to several Western European economies, these trends have been accompanied by weaker institutional protections and greater employer discretion in shaping employment conditions (Csaba, 2022; Daskalova, 2020). While comparable cross-country evidence varies, these developments are broadly consistent with observed shifts in labour market structures in other transition economies.

By strengthening employer discretion in labour utilization, concentrated market structures shift adjustment costs and employment risks onto workers. Taken together, these dynamics indicate that corporate concentration restructures the contractual and temporal dimensions of employment while reinforcing employer discretion beyond wage-setting mechanisms.

Based on these arguments, the following hypotheses are proposed:

H2a. 

Higher corporate concentration is associated with a higher share of part-time employment.

H2b. 

Higher corporate concentration is associated with longer overtime hours.

The empirical specification is as follows:

$$WorkingConditio{n}_{it}={\beta }_{2}HH{I}_{it}+{\mu }_i+{\lambda }_t+{\epsilon }_{it}$$

where the dependent variable represents the following:

• Overtime hours
• Paid holidays
• Supplementary compensation

Expected signs:

• Overtime: ${\beta }_2>0$
• Paid holidays: ${\beta }_2<0$
• Supplementary compensation: ${\beta }_2<0$

2.3. Corporate Concentration and Workers’ Rights & Job Quality

This section examines broader dimensions of job quality and workers’ rights. Beyond wage-setting mechanisms and employment flexibility, the literature suggests that corporate concentration also affects non-wage aspects of employment and the strength of institutional protections (Clapp, 2021, 2022; Hildebrandt, 2006).

As labour market concentration increases, workers outside employment options decline, leading to a weakening of bargaining power. In such contexts, dominant firms acquire greater discretion in determining working conditions, employment standards, and contractual arrangements. The consequences of monopsony power therefore extend beyond wage suppression to encompass the erosion of formal protections and the reduction of non-wage benefits (Passerini, 2025).

Paid leave represents a fundamental indicator of workers’ rights and formal employment protection. In competitive markets, such entitlements are typically secured through legal regulation, institutional oversight, and collective bargaining arrangements. However, under concentrated market conditions where employer power is reinforced, and institutional constraints are comparatively weaker, firms may limit the scope, duration, or accessibility of paid leave as part of broader labour cost management strategies (Chinetti, 2025; Zhou, 2024).

In addition to paid leave, supplementary compensation components, such as allowances and non-wage benefits beyond base salary and regular bonuses, serve as important indicators of job quality and employment security. In competitive environments, these benefits function as tools to attract and retain workers. By contrast, evidence suggests that in concentrated markets, concentrated firms are more likely to standardize, restrict, or reduce these supplementary benefits in order to contain labour costs and preserve managerial flexibility (Brunt & Bowblis, 2017; Qiu & Sojourner, 2023).

Moreover, the distribution of non-wage benefits increasingly becomes selective and discretionary in concentrated settings, often favouring managerial or higher-skilled employees. This selective allocation contributes to widening inequalities in working conditions and may reduce overall job quality within firms (Passerini, 2025).

Higher levels of corporate concentration have also been associated with declines in broader job-quality indicators, including income stability, job security, and work–life balance (Chinetti, 2025). Although collective protections and labour market institutions can mitigate these adverse effects, rising concentration may weaken the effectiveness of regulatory frameworks and unions, thereby expanding firms’ capacity to redesign employment conditions to their advantage (Clapp, 2021; Zhou, 2024).

Taken together, the literature indicates that corporate concentration influences workers’ rights and job quality not only through wage restraint but also through the restructuring of non-wage benefits and the weakening of institutional safeguards. By reinforcing employer discretion in concentrated markets, firms can limit paid leave entitlements and reduce supplementary compensation while framing these adjustments as necessary components of labour cost management.

Based on these arguments, the following hypotheses are proposed:

H3a. 

Higher corporate concentration is associated with a lower number of paid leave days.

H3b. 

Higher corporate concentration is associated with lower levels of supplementary compensation.

Empirical specification:

$$PartTimeShar{e}_{it}={\beta }_{3}HH{I}_{it}+{\mu }_i+{\lambda }_t+u_{it}$$

Expected sign:

$${\beta }_3>0$$

3. Methodology and Data

3.1. Data Collection and Categorization

The Hungarian food industry’s industry-level data from 1993 to 2022 are used in this study. Three main sources provided the data: (1) a national dataset gathered by Central European University (CEU); (2) the KRTK Databank “HUN-REN Hungarian Research Network database” (accessed on 6 May 2025); and (3) the STATISTA database (accessed on 6 May 2025). The database includes comprehensive data on a variety of food industry subsectors, including production, employment, value added, wages, bonuses, working-time arrangements, and employment structures. A structural analysis of corporate concentration and its connection to labour market outcomes over a 30-year period is made possible by the level of analysis carried out at both the subsector and industry levels.

The unit of observation in this study is defined as a subsector–year panel. Each observation corresponds to a specific food industry subsector in a given year over the period 1993–2022. The final dataset therefore consists of a balanced panel of 120 observations (4 subsectors × 30 years).

Each subsector is made up of a group of companies that work in the Hungarian food industry. The concentration measures are derived from firm-level market shares within each subsector; however, the empirical analysis is performed at the aggregated subsector level due to limitations in data availability. Consequently, individual firm-level observations are not directly discernible in the dataset.

The chosen period includes significant institutional, political, and economic changes that occurred in Hungary after the country moved from a centrally planned communist system to a market-oriented economy and democratic government. In order to avoid incomplete and untrustworthy records from the early post-communist transition period, the beginning year (1993) was chosen based on data availability, accessibility, validity, reliability, and comprehensiveness. Comprehensive and verified data on important labour-related variables were only available through 2022, despite the original goal of extending the dataset through 2024. As a result, the empirical analysis ends in 2022 because the data for the following years is still lacking.

The Hungarian food industry saw significant changes in ownership structures and competitive conditions during this time, as well as widespread privatization, a notable increase in foreign direct investment, and the country’s 2004 EU accession. The chosen time frame is especially appropriate for examining trends in corporate concentration and their effects on the labour market because of these long-term developments.

Section 3.2 and Section 3.3 go into great detail about measuring corporate concentration and labour market outcome variables. Hungary’s export-oriented growth model, the food industry’s strategic importance for employment, value added creation, and supply chain organization led to its selection. This study focuses on four major subsectors; the selection of these four subsectors is intentional and driven by the study’s focus on environments with the highest levels of corporate concentration. Including all nine subsectors would introduce substantial heterogeneity in market structure, potentially obscuring the relationship between corporate concentration and labour market outcomes. By focusing on the most concentrated subsectors, the analysis provides a clearer and more consistent empirical setting for identifying the mechanisms through which concentration affects wages and working conditions, like cereals and cereal products, food processing, oils and fats, and sugar and confectionery that exhibit the highest levels of corporate concentration among the nine subsectors of the Hungarian food industry, based on standard market concentration indicators. Detailed sector categorization can be seen in Figure 1.

3.2. Measuring Corporate Concentration

The Herfindahl–Hirschman Index (HHI), introduced by Hirschman (Hirschman, 1945) and Herfindahl (Herfindahl, 1963), serves as a tool to measure corporate concentration. This study uses the Herfindahl–Hirschman Index (HHI) as the primary measure of market concentration. For a market with n firms, where the market share of firm j is $s_j$; the HHI is calculated as the sum of the squares of the market shares:

$$HHI=\sum _{j=1}^n{s}_j^2$$

while this study used percentages (0 < $s_i$ ≤ 100) market shares are typically expressed as fractions. As a result, the HHI falls between 0 and 10,000. It represents the distribution of firm sizes within a market, with a single dominant firm reaching its maximum value of 10,000 and many small firms of equal size approaching zero. As the number of businesses declines or their market share gap widens, the HHI rises (Ericsson et al., 2024; Johnston et al., 2024). There are general guidelines for corporate concentration levels, even though the exact numerical thresholds are not always set. For example, the U.S. Department of Justice and the Federal Trade Commission (2010) divide markets into three groups:

• Unconcentrated Markets: HHI below 1500
• Moderately Concentrated Markets: HHI between 1500 and 2500
• Highly Concentrated Markets: HHI above 2500

The European Commission (2004) also uses the HHI to evaluate corporate concentration and horizontal mergers, with some methodological variations. Since the HHI calculation squares each firm’s percentage market share, smaller firms have limited influence on the overall HHI. Their contribution diminishes rapidly as their market share decreases. Therefore, a complete HHI can often be estimated using the market shares of the largest firms and the total market size to approximate the cumulative share of smaller participants (Cao et al., 2023; Ericsson et al., 2024; Johnston et al., 2024). As a result, the following table and figure show how corporate concentration changed between 1993 and 2022 across a selected Hungarian food manufacturing subsector, as determined using the HHI (Figure 1).

Table 1. Herfindahl–Hirschman Index (HHI) by subsector and period (period averages, 1993–2022).

Time Period	Industry Subsector	Corporate Concentration Index (HHI)	Market Structure
1993–1998 1993–1998 1993–1998 1993–1998	cereals and cereal products food processing oil and fats sugar and confectionery	5808 2573 6585 3073	Highly Concentrated Markets Highly Concentrated Markets Highly Concentrated Markets Highly Concentrated Markets
1999–2004 1999–2004 1999–2004 1999–2004	cereals and cereal products food processing oil and fats sugar and confectionery	4196 4412 8746 4670	Highly Concentrated Markets Highly Concentrated Markets Highly Concentrated Markets Highly Concentrated Markets
2005–2010 2005–2010 2005–2010 2005–2010	cereals and cereal products food processing oil and fats sugar and confectionery	3045 4200 7872 6332	Highly Concentrated Markets Highly Concentrated Markets Highly Concentrated Markets Highly Concentrated Markets
2011–2016 2011–2016 2011–2016 2011–2016	cereals and cereal products food processing oil and fats sugar and confectionery	2882 3877 7176 7074	Highly Concentrated Markets Highly Concentrated Markets Highly Concentrated Markets Highly Concentrated Markets
2017–2022 2017–2022 2017–2022 2017–2022	cereals and cereal products food processing oil and fats sugar and confectionery	2089 3819 4785 7097	Moderately Concentrated Markets Highly Concentrated Markets Highly Concentrated Markets Highly Concentrated Markets

shows consistently high levels of corporate concentration across the selected subsectors of the Hungarian food manufacturing industry. The HHI values are consistently well above the conventional threshold for highly concentrated markets, indicating the dominance of a small number of firms in all observed periods. Notably, in eight of the twenty subsector–period observations, the implied minimum market share of the largest firm exceeds 50%, suggesting substantial dominance within these markets.

HHI values represent average concentration levels within each subsector over the specified time periods. The Herfindahl–Hirschman Index (HHI) is the primary measure of corporate concentration used in this study. CR4 refers to the concentration ratio of the four largest firms, although it is not the main indicator used in the analysis.

The time periods are grouped into multi-year intervals to smooth short-term fluctuations and improve the interpretability of long-term trends in corporate concentration.

Although some variation is observed over time, including a modest decline in concentration in certain subsectors during the later period (2017–2022), the overall market structure remains highly concentrated. These patterns provide important context for the empirical analysis, indicating that labour market outcomes are shaped within environments characterized by strong market power and limited competitive pressure.

Therefore, CR4 is commonly used as an alternative concentration measure; this study relies primarily on the HHI due to its ability to capture the full distribution of firm market shares.

3.3. Labour Market Outcome Variables

Three primary dimensions and eight sub-dimensions that directly capture and reflect corporate concentration and employer monopsony power in labour markets are used to categorize labour market outcomes in this study. The chosen variables are intended to address various facets of working conditions in the Hungarian food industry, such as work intensity, job quality, labour flexibility, and compensation structures.

Four sub-variables make up the first dimension, Wage Level and Core Earnings: base hourly wages, regular bonuses, non-regular bonuses, and gross monthly earnings. The main measure of fixed compensation is base hourly wages at the subsector level. While irregular bonuses include indirect, discretionary, and unpredictable payments that are usually given outside of formal wage-setting procedures and collective bargaining frameworks, regular bonuses are defined as predictable and periodic payments made to employees. In order to examine structural changes in earnings composition and overall worker compensation, gross monthly earnings offer a more comprehensive measure of total income. All variables related to wages are given in nominal terms and measured at the subsector level. Base hourly wages are given in Euro per hour, and gross monthly earnings, regular bonuses, and non-regular bonuses are given in Euro per month.

The percentage of share of part-time employment and overtime hours are the two sub-variables used to measure the second dimension, Work Intensity and Flexibility. While overtime hours are a measure of labour intensity and work pressure, the percentage of part-time workers indicates the degree of employment flexibility and employment uncertainty within each subsector.

Two sub-variables are used to evaluate the third dimension, Workers’ Rights and Job Quality: Paid holidays and Supplement to salary. While supplemental wage-related benefits capture the scope of non-wage coverage and the general quality of employment conditions, paid leave is used as a stand-in for institutional protections and workers’ rights.

The study’s conceptual framework is shown in Figure 2 below. Three important aspects of labour market outcomes, wage level and earnings structure, work intensity and flexibility, and workers’ rights and job quality, are shown in the figure to be influenced by company concentration as the main explanatory variable. A systematic empirical analysis of how corporate concentration affects employment conditions throughout the chosen subsectors of the Hungarian food industry is made possible by the operationalization of each dimension through particular, quantifiable sub-variables.

4. Empirical Results

This section presents the empirical findings of the study. The analysis proceeds in four stages. First, descriptive statistics provide an overview of wage structures and earnings dispersion. Second, the evolution of corporate concentration over time is examined (H1). Third, panel regression models are employed to assess the relationship between concentration and both wage and non-wage labour market outcomes (H2–H4). Finally, a combined specification is estimated to explore potential mediation effects.

4.1. Descriptive Analysis

This subsection provides a descriptive overview of wage structures and earnings distribution across the four selected subsectors of Hungary’s food industry over the period 1993–2022. The aim is to identify preliminary patterns in wage dispersion and income composition prior to the multivariate analysis.

Table 2. Descriptive Statistics of Wage Variables (Euro/hour and Euro/month).

Industry	Mean Hourly Wage (Earnings)	Mean Gross Monthly (Earnings)	Standard Deviation (Earnings)	Minimum (Earnings)	Maximum (Earnings)
Cereals and Products	2.93	228	215	15	730
Food Processing	4.63	225	188	15	665
Oils and Fats	3.00	241	153	10	540
Sugar and Candies	3.80	239	155	15	570

Notes: Mean hourly wage is measured in Euro per hour. Gross monthly earnings are measured in Euro per month. Standard deviation, minimum, and maximum refer to gross monthly earnings unless otherwise specified.

reports mean hourly wages, mean gross monthly earnings, and dispersion measures across subsectors. Substantial variation is observed in average hourly wages. Food processing exhibits the highest mean hourly wage (4.63), while cereals and cereal products record the lowest (2.93). However, despite this variation in base wages, mean gross monthly earnings remain relatively similar across sectors, ranging between 225 and 241.

This divergence between hourly wages and total earnings suggests that fixed wage components alone do not fully explain income formation. Instead, additional compensation elements such as bonuses and supplementary payments likely play an important role in shaping overall earnings.

Measures of dispersion further reveal considerable within-sector inequality. High standard deviations and wide ranges between minimum and maximum earnings indicate substantial heterogeneity in compensation structures. For example, the cereals subsector shows earnings ranging from 15 to 730, reflecting the coexistence of relatively low-paid and high-income positions within the same industrial segment.

Importantly, minimum earnings remain comparatively low across all subsectors, suggesting the persistence of lower-wage employment even in capital-intensive and highly concentrated industries. However, part of the observed dispersion may also reflect differences in working-time arrangements, including variations in hours worked and overtime intensity across subsectors. In addition, as earnings are reported in nominal terms over a long time period (1993–2022), part of the variation may be influenced by wage inflation, largely reflecting underlying price dynamics. While descriptive statistics do not establish causal relationships, these preliminary patterns are consistent with the possibility that compensation structures differ across sectors in ways not captured solely by base wage levels.

The descriptive statistics presented in

Table 3. Descriptive statistics regular and non-regular bonus.

Industry	Regular Bonus Mean	Regular Bonus SD	Non-Regular Bonus Mean	Non-Regular Bonus SD
Cereals and Products	160.4	159.46	450.14	438.06
Food Processing	200.87	153.81	662.56	646.36
Oils and Fats	232.36	148.62	718.33	677.48
Sugar and Candies	943.43	813.84	943	814

provide a detailed picture of wage structures, earnings composition, and corporate concentration across the four subsectors, Cereals and Products, Food Processing, Oils and Fats, and Sugar and Candies over the period 1993–2022.

A key insight emerges from the analysis of bonus structures. Regular bonuses average 160.40 € in Cereals, 200.87 € in Food Processing, and 232.36 € in Oils and Fats, indicating that structured, predictable bonuses are more prominent in the latter sectors. However, the Sugar and Candies subsector stands out dramatically, with an exceptionally high mean regular bonus of 943.43 € and a very large standard deviation of 813.84. This suggests extreme variability and a strong reliance on bonus-based compensation.

For non-regular (irregular) bonuses, the averages are also substantial: 450.14 € in Cereals, 662.56 € in Food Processing, 718.33 € in Oils and Fats, and even higher dispersion in Sugar and Candies (with a maximum reaching 2400 €). The high standard deviations, 438.06, 646.36, and 677.48, respectively, indicate that these payments are highly volatile and unevenly distributed. This reinforces the idea that firms increasingly rely on flexible, performance-based compensation mechanisms rather than stable wages.

Overall, the descriptive analysis reveals three major patterns. First, base wages differ significantly across sectors, with Food Processing leading and Cereals lagging behind. Second, gross earnings are relatively similar despite wage differences, indicating that bonuses and supplements play a compensatory role. Third, and most importantly, earnings variability is high across all sectors, driven largely by irregular bonus payments and differing employment structures. These findings support the broader argument that corporate concentration does not simply reduce wages, but reshapes the entire compensation structure. Workers in more concentrated sectors appear to rely more heavily on variable income components, leading to greater income uncertainty and inequality, even when average earnings remain stable. The descriptive evidence points to a relative decoupling between hourly wages and total earnings, as well as significant intra-sector dispersion. Part of this divergence may be associated with differences in working-time arrangements, including variations in hours worked and overtime intensity across subsectors. These aspects are examined more explicitly in the subsequent analysis of working-time variables.

These findings motivate the subsequent regression analysis, which formally evaluates the relationship between corporate concentration and labour market outcomes.

4.2. Stationarity Tests

Panel unit-root tests to assess the stationarity properties of the key variables prior to estimation. For the corporate concentration measure (Herfindahl–Hirschman Index, HHI) we report the Levin–Lin–Chu (LLC) and Im–Pesaran–Shin (IPS) tests. The LLC test yields a test statistic z = −0.522 with p = 0.03007, which allows rejection of the null hypothesis of a unit root at the 5% significance level, indicating that HHI is stationary in levels. The IPS test could not be reliably computed for our sample (warning/NA) due to the small cross-sectional dimension (N = 4); IPS is known to be less reliable when N is very small. Given the small cross-section, we place primary weight on the LLC result, which has greater power in panels with limited cross-sectional units. In sum, the evidence supports that the HHI series is I (0) and can be used in level form in the panel regressions. Therefore, differencing is unnecessary and the risk of spurious regression induced by non-stationarity is low; fixed-effects.

4.3. Evolution of Corporate Concentration (H1)

To evaluate Hypothesis 1, which examines whether corporate concentration increased over the period 1993–2022, a fixed-effects panel regression model was estimated. The Herfindahl–Hirschman Index (HHI) serves as the dependent variable, while a linear time trend captures overall temporal dynamics. Sector fixed effects are included to account for time-invariant structural differences across subsectors.

Table 4. Panel Unit Root Tests for Corporate Concentration (HHI).

Variable	Test (Specification)	Test Statistic	p-Value	Conclusion
HHI	Levin–Lin–Chu (exo = trend)	z = −0.522	0.03007	Reject unit root (stationary in levels)
HHI	Im–Pesaran–Shin (exo = trend)	—	NA/warning	Not reliably computed (N = 4); IPS less reliable for small N

reports the estimated time coefficients for both the overall fixed-effects model and the sector-specific linear trends.

Table 5. Trend in Corporate Concentration (HHI).

Panel A: Overall Fixed-Effects Model
Variable	Coefficient	Robust Std. Error	t-Value	p-Value
Year	−24.68	139.52	−0.18	0.862
Panel B: Sector-Specific Linear Trends
Sector	Coefficient (Year)	Std. Error	t-Value	p-Value
Cereals	−143.31	25.51	−5.62	<0.001
Food Processing	30.47	21.40	1.42	0.165
Oil and Fats	−92.88	41.22	−2.25	0.032

presents the estimated time trends in corporate concentration, measured using the Herfindahl–Hirschman Index (HHI). Panel A reports the results from a within (fixed-effects) panel model, where the coefficient on the time variable captures the overall trend in concentration across subsectors over the period 1993–2022. The estimated coefficient is not statistically significant, indicating the absence of a uniform trend in corporate concentration at the aggregate level.

Panel B reports subsector-specific linear time trends, revealing substantial heterogeneity across subsectors. Cereals and oils and fats exhibit statistically significant negative trends, whereas sugar and confectionery show a strong positive and significant trend. In contrast, the coefficient for food processing is not statistically significant, suggesting no clear trend in that subsector.

All models are estimated using robust standard errors (HC1), and statistical significance is assessed at conventional levels.

As shown in Figure 3, the overall trend is not statistically significant. This suggests that, on average, corporate concentration did not exhibit a systematic upward trajectory across the Hungarian food industry during the period under consideration.

However, the sector-specific estimates reveal notable heterogeneity. Concentration declined significantly in the cereals subsector and in oils and fats, whereas a statistically significant upward trend is observed in sugar and confectionery. The food processing subsector does not display a statistically meaningful linear trend.

These findings indicate that structural changes in market concentration have not followed a uniform pattern across the industry. Rather than experiencing a generalized increase in concentration, subsectors appear to have undergone differentiated consolidation dynamics.

Accordingly, Hypothesis 1 is not supported at the aggregate industry level but receives partial support in the case of sugar and confectionery, where concentration increased significantly over time.

4.4. Wage Structure and Earnings Trends

The figures presented in this section depict sector-level average gross monthly earnings. Each observation represents the average earnings within a given subsector and year over the period 1993–2022. The horizontal axis corresponds to calendar years, and the label “Year (CC)” has been simplified to “Year” for clarity. The plotted values are constructed using aggregated subsector-level data.

The analysis is based on a panel data framework, where subsectors (j) constitute the cross-sectional dimension and years (t) the time dimension. The models are estimated using fixed-effects panel regressions rather than simple OLS.

A trend analysis of gross monthly income over time shows non-linear and fluctuating patterns across all four sectors. Nominal earnings have remained broadly stable, but short-term fluctuations are frequent, indicating that income dynamics are heavily influenced by bonuses and irregular payments rather than by sustained wage growth. The absence of a clear upward trend in any of the sectors suggests that productivity gains or market consolidation have not translated into a sustained increase in the earnings of the workforce. Instead, wage volatility seems to be a defining characteristic of employment in these sectors, in line with a wage structure that favours flexibility over stability.

As shown in Figure 4 the evolution of gross monthly earnings in the sugar and confectionery subsector exhibits a pronounced upward trend in the later years of the sample period, accompanied by substantial short-term fluctuations. While earnings increase markedly at certain points, the presence of sharp declines and volatility suggests that income dynamics in this subsector are highly sensitive to irregular payments and variable compensation components. This pattern is consistent with a compensation structure in which bonuses and supplementary payments play a significant role.

As shown in Figure 5, earnings in the food processing subsector display considerable volatility over time, with no clear long-term trend. Periods of rapid increases are followed by abrupt declines, indicating substantial instability in income levels. This pattern suggests that earnings are influenced by cyclical or short-term factors rather than sustained wage growth, potentially reflecting fluctuations in working hours, bonuses, or firm-level performance.

As shown in Figure 6, The oils and fats subsector shows an initial period of relatively high earnings followed by a gradual decline over time, interspersed with episodes of sharp variation. Although earnings appear to stabilize at lower levels in later periods, the observed fluctuations indicate persistent heterogeneity in compensation. This may reflect structural changes in the subsector, including shifts in production, employment composition, or compensation practices.

The cereals and cereal products subsector is characterized by a clear downward trend in gross monthly earnings over the sample period. This decline is accompanied by periods of short-term variability, particularly in the earlier years. In later periods, earnings stabilize at relatively low levels, suggesting a compression of income and potentially reflecting changes in labour demand, productivity, or wage-setting mechanisms within the subsector.

As shown in Figure 7, the trend analysis of gross monthly earnings reveals pronounced volatility and non-linear dynamics across all four subsectors. While the data are plotted in chronological order to reflect year-to-year variation, the observed patterns should not be interpreted as smooth or continuous trends. Instead, the figures highlight substantial short-term fluctuations, suggesting that earnings are primarily driven by variable compensation components such as bonuses and irregular payments, rather than sustained increases in base wages.

The absence of a consistent upward trajectory indicates that structural changes in the industry, including rising corporate concentration, have not translated into stable long-term wage growth. Rather, the evidence points to a compensation structure characterized by flexibility and adjustment mechanisms, where firms rely on performance-related pay and variable compensation to adapt to changing conditions.

To further examine the determinants of earnings, gross monthly income is regressed separately for each subsector on base hourly wages, regular bonuses, and non-regular bonuses. These specifications are estimated using ordinary least squares (OLS) models. This empirical approach provides insight into how different components of compensation contribute to overall earnings and reflects the wage and earnings dimension of the conceptual framework.

4.4.1. Sugar and Candies

In the sugar and candies sector, regular bonuses are the dominant determinant of earnings, while base wages play no statistically meaningful role. This indicates a compensation regime in which firms use bonuses to reward labour without committing to permanent wage increases. The negative effect of non-regular bonuses suggests income volatility, reflecting fluctuating workloads and irregular working hours (

Table 6. Regression Results—Sugar and Candies.

Variable	Coefficient	Std. Error	t-Value	Significance
Base Hourly Wage	12.63	19.37	0.65	Not significant
Regular Bonuses	0.93	0.07	13.84	Significant
Non-Regular Bonuses	−0.01	0.01	−2.11	Significant
R2	0.987

Notes: Standard errors are reported in the second column. Significant p < 0.05.

).

The regression results indicate that regular bonuses are the primary determinant of gross monthly earnings in the sugar and candies industry. The coefficient implies that increases in regular bonuses translate almost one-to-one into higher monthly earnings. In contrast, the base hourly wage has no statistically significant effect, suggesting that wages are relatively rigid or play a limited role in determining total compensation.

The negative and statistically significant coefficient for non-regular bonuses suggests that reliance on irregular payments may introduce income instability, possibly reflecting fluctuating workloads or performance-based compensation. The exceptionally high R² value indicates that earnings are almost entirely explained by the compensation structure, underscoring the dominance of firm-level pay policies.

4.4.2. Food Processing

Food processing shows a highly standardized compensation structure. Earnings are almost entirely dependent on regular bonuses, with basic salaries being statistically insignificant. This indicates strong coordination between employers and wage-setting power, which is typical of highly concentrated sectors. Workers’ earnings are therefore closely linked to company-defined bonus schemes rather than to wage increases negotiated by the employer. In the food processing sector, regular bonuses are by far the dominant factor in the formation of income, with a coefficient that exceeds unity. This result suggests that companies rely heavily on structured bonus schemes to reward employees, which may be linked to output targets or the company’s profitability. Neither basic salaries nor irregular bonuses have a significant impact on earnings, which indicates a highly standardized compensation system. This structure is consistent with concentrated industries where firms exercise strong control over wage setting and restrict the bargaining power of workers (

Table 7. Regression Results—Food Processing.

Variable	Coefficient	Std. Error	t-Value	Significance
Intercept	−15.28	10.34	−1.48	Not significant
Base Hourly Wage	−0.33	1.11	−0.30	Not significant
Regular Bonuses	1.21	0.04	29.83	Significant
Non-Regular Bonuses	−0.00	0.01	−0.28	Not significant
R2	0.978

).

4.4.3. Oils and Fats

The oil and fats sector shows a negative correlation between basic wages and profits, which points to a substitution effect. Higher wages are compensated by lower bonuses and working hours, indicating that firms are tightly controlling total labor costs. This model is in line with increased workload and flexible scheduling, which reinforces the role of company concentration in changing working time patterns. A characteristic feature of this sector is a negative and significant coefficient for basic hourly wages. This indicates a substitution effect, whereby the increase in hourly wages is offset by a reduction in the premium or working time. This model reflects the strong control exercised by the employer over the overall cost of labour and supports the emphasis of the conceptual model on work intensity and flexibility. Regular bonuses remain strongly positive and substantial, reinforcing the centrality of the variable remuneration mechanism (

Table 8. Regression Results—Oils and Fats.

Variable	Coefficient	Std. Error	t-Value	Significance
Intercept	26.68	11.10	2.40	Significant
Base Hourly Wage	−19.57	8.51	−2.30	Significant
Regular Bonuses	1.18	0.07	16.57	Significant
Non-Regular Bonuses	−0.00	0.00	−0.46	Not significant
R2	0.994

).

4.4.4. Cereals

Unlike in other subsectors, the basic wage in the cereals sector remains a major determinant of earnings, which suggests that there is some wage protection, possibly due to stronger regulation or to historical collective bargaining institutions. However, the continued negative impact of irregular bonuses points to continued income volatility and uneven working hours. Unlike in other sectors, the cereal sector has a significant impact on earnings in the form of both basic salaries and periodic bonuses. This suggests relatively stronger wage-setting mechanisms, possibly as a result of regulatory supervision or partial unionization. However, the negative impact of irregular bonuses again highlights income volatility.

4.5. Corporate Concentration and Wage Outcomes (H2)

To evaluate Hypothesis 2, two-way fixed-effects panel regressions are estimated, controlling for both sector and year effects. This specification accounts for time-invariant sectoral heterogeneity and common macroeconomic shocks across periods.

Table 9. Regression Results—Cereals.

Variable	Coefficient	Std. Error	t-Value
Intercept	−63.16	10.25	−6.16
Base Hourly Wage	55.41	5.26	10.54
Regular Bonuses	0.88	0.05	17.68
Non-Regular Bonuses	−0.03	0.01	−2.75
R2	0.991

reports the estimated association between the Herfindahl–Hirschman Index (HHI) and wage-related outcomes.

The results indicate a statistically significant negative association between corporate concentration and both base hourly wages and gross monthly earnings. The estimated coefficients suggest that higher levels of concentration are correlated with lower wage outcomes, even after controlling for sector-specific and time-specific fixed effects.

Given the log-linear specification, the magnitude of the coefficient implies that a 1000-point increase in HHI is associated with approximately a 10.6 percent decrease in base wages. A similar negative relationship is observed for gross monthly earnings.

While these findings are consistent with theoretical models of labour market concentration, they should be interpreted as conditional associations rather than definitive causal effects. The results suggest that higher concentration levels coincide with weaker wage performance across subsectors.

Accordingly, Hypothesis 2 receives empirical support in terms of the observed negative relationship between corporate concentration and wage outcomes.

4.6. Corporate Concentration and Non-Wage Working Conditions (H3)

Hypothesis 3 examines whether higher levels of corporate concentration are associated with changes in non-wage working conditions. To test this hypothesis, panel regressions are estimated using overtime hours and paid holidays as dependent variables, with the Herfindahl–Hirschman Index (HHI) as the key explanatory variable.

The results indicate a statistically significant positive association between concentration and overtime hours. The estimated coefficient suggests that higher levels of HHI are correlated with increased labour utilisation within subsectors.

In contrast, a statistically significant negative relationship is observed between concentration and paid holidays. This finding implies that higher concentration levels are associated with fewer days of paid leave.

Taken together, the results suggest that greater corporate concentration coincides with changes in non-wage dimensions of employment. While the estimates do not establish causality, they are consistent with the hypothesis that labour conditions vary systematically with market concentration levels.

Accordingly, Hypothesis 3 receives empirical support in terms of the observed associations between concentration, overtime intensity, and paid leave provision.

4.7. Corporate Concentration and Part-Time Employment (H4)

Hypothesis 4 evaluates whether higher levels of corporate concentration are associated with changes in non-standard employment arrangements, measured as the share of part-time employees within each subsector. A two-way fixed-effects panel regression model is estimated, controlling for sector and year effects.

The results indicate a statistically significant positive association between corporate concentration and the share of part-time employment. The estimated coefficient suggests that higher HHI levels are correlated with a greater prevalence of part-time work across subsectors. While the magnitude of the coefficient is modest in absolute terms, the relationship remains statistically robust. These findings suggest that variations in market concentration coincide with observable differences in employment structure.

It is important to note that the regression identifies conditional associations rather than causal effects. Nevertheless, the direction and statistical significance of the estimates provide empirical support for Hypothesis 4. However, part-time employment is also considered as a potential channel through which corporate concentration may affect broader labour market outcomes, a mechanism that is further explored in the combined specification.

4.8. Descriptive Analysis of Earnings Composition (Base Wage vs. Bonuses)

Descriptive statistics reveal a highly unequal and structurally unbalanced composition of income in the Hungarian food industry, with a clear distinction between fixed remuneration (basic hourly wage) and variable remuneration (regular and irregular bonuses).

4.8.1. Base Hourly Wages (Fixed Component)

Basic hourly wages are the most stable component of earnings, with a mean of around 3.59 and a median of 3.62, suggesting a relatively symmetric distribution around the centre of the trend. However, the wide range—from 0.92 to 30.00—indicates considerable diversity between sub-sectors and time periods. Despite these differences, the basic wage seems relatively depressed compared to other income components. The small difference between the mean and median indicates a limited skewness, which means that the majority of observations are clustered in a narrow range. This supports the view that wages are institutionally capped and less responsive to market fluctuations, which is probably reflected in formal wage-setting mechanisms or sectoral agreements. Graphical evidence supports this interpretation: the basic wage shows only slight and irregular changes over time, with no clear upward trend. This indicates that wage growth was structurally limited, even in the context of changing market conditions.

4.8.2. Regular Bonuses (Predictable Variable Pay)

Periodic bonuses, defined as regular and predictable payments, show a higher degree of variation than basic salaries. With an average of about 197.9 and a median of 167.5, the distribution is slightly skewed to the right, suggesting that higher bonuses are found in certain sectors or periods. This range—between 15.07 and 575.00—shows that regular bonuses can be a significant contributor to earnings, although their presence is not uniform across the data set, as evidenced by the high number of missing observations. Compared to base salaries, regular bonuses show more pronounced fluctuations over time, indicating that they are used by companies as a flexible adjustment mechanism. However, their relatively structured nature means that they are still partly embedded in formal pay schemes, such as performance-based incentive schemes and contractual bonuses.

4.8.3. Non-Regular Bonuses (Irregular and Discretionary Pay)

As shown in Figure 8, non-regular bonuses are the most variable and predominant component of variable remuneration. With an average of approximately 693.6 and a median of 400.0, this category shows a highly skewed distribution, with extreme values as high as 2540.0. The large gap between the median and the maximum level indicates the existence of significant outliers, which reflect irregular and discretionary payments that may significantly increase earnings in some years or sectors. This high variation underlines the unpredictable nature of irregular bonuses, which are not bound by fixed timetables or formal agreements. The graphical trends show sharp fluctuations over time, confirming that irregular bonuses are highly sensitive to decisions made at the firm level and to market conditions. This suggests that companies are increasingly relying on discretionary payments to adjust labour costs rather than on changes in basic salaries.

4.9. Combined Model and Mediation Effects

Before presenting the combined specification, it is important to clarify the modelling strategy. The baseline models reported in

Table 10. Concentration and Wage Outcomes (Two-Way Fixed Effects).

Dependent Variable	HHI Coefficient	Std. Error	p-Value	Interpretation
Log Base Wage	−1.06 × 10−4	1.65 × 10−5	<0.001	Strong negative
Log Earnings	−6.47 × 10−5	1.97 × 10−5	0.001	Negative

,

Table 11. Concentration and Working Conditions.

Dependent Variable	HHI Coefficient	Std. Error	p-Value	Expected Sign	Result
Overtime Hours	+0.00455	0.00070	<0.001	Positive	Supported
Paid Holidays	−0.00220	0.00022	<0.001	Negative	Supported

and

Table 12. Concentration and Part-Time Employment.

Dependent Variable	HHI Coefficient	Std. Error	p-Value
Part-Time Share	+1.01 × 10−5	1.62 × 10−6	<0.001

are intentionally estimated separately to capture the total (reduced-form) association between corporate concentration and each labour market outcome. Estimating a fully combined model including all variables simultaneously may introduce a “bad control” problem, as several working-condition variables (e.g., overtime, part-time employment, and supplementary compensation) are themselves outcomes of corporate concentration and therefore lie on the causal pathway. Conditioning on these variables would absorb part of the effect of concentration and potentially bias the estimated coefficient downward.

To further examine the relationship between corporate concentration and earnings, an extended two-way fixed-effects specification is estimated in which working condition variables are included alongside the Herfindahl–Hirschman Index (HHI). This approach allows for an assessment of whether the association between concentration and earnings remains statistically significant after accounting for overtime, part-time employment, and supplementary compensation components.

The results indicate that once working condition variables are incorporated into the model, the coefficient on HHI becomes statistically insignificant. The loss of statistical significance of the HHI coefficient in the combined model should therefore not be interpreted as evidence against the existence of an effect. Rather, it suggests that the relationship between corporate concentration and earnings operates indirectly through adjustments in working-time arrangements and employment structure. This result is consistent with a mediation mechanism, where concentration affects intermediate labour market variables, which in turn shape overall earnings. Accordingly, the combined specification is used as a complementary analysis to explore potential channels, rather than as a substitute for the baseline models.

In contrast, supplementary compensation remains positively and significantly associated with gross monthly earnings. These findings suggest that the previously observed association between concentration and earnings may reflect the role of compensation structure and employment characteristics. However, given the observational nature of the analysis, the estimates should be interpreted as conditional associations rather than evidence of a formal causal mediation mechanism.

Overall, the combined specification underscores the importance of compensation composition in explaining earnings variation across subsectors. While concentration exhibits a statistically significant association with wages in baseline models, this relationship appears sensitive to the inclusion of employment structure variables.

Overall, the empirical findings indicate that corporate concentration has not followed a uniform upward trajectory across subsectors. The results reveal statistically significant associations between concentration and wage outcomes, as well as systematic relationships with non-wage working conditions and part-time employment.

The relatively high R² values observed in the regression models may raise concerns regarding potential spurious correlations driven by common trends. However, several factors mitigate this risk. First, panel unit root tests indicate that the key variables are stationary in levels. Second, the inclusion of time fixed effects controls for common macroeconomic trends affecting all subsectors. Third, the consistency of results across alternative model specifications suggests that the estimated relationships reflect meaningful economic associations rather than purely statistical artefacts.

Higher levels of concentration are associated with lower wages, increased overtime intensity, fewer paid holidays, and a greater prevalence of part-time employment. Although causal effects cannot be established, the observed patterns highlight meaningful differences in labour market outcomes across subsectors characterized by varying degrees of market concentration.

Empirical results show that mergers have a significant but complex impact on labour market outcomes in the Hungarian food industry. Overall, H1a is supported by the fact that higher concentration (HHI) is correlated with lower base hourly wages. This relationship becomes statistically significant when robust standard errors are applied, suggesting that firms in concentrated markets may be able to lock in fixed wages. In the cases of H1b and H1c, evidence points to a change in the compensation structure rather than a simple salary reduction. Regular bonuses do not increase with concentration, whereas irregular (unregular) bonuses seem to play a bigger role. This suggests that companies rely more on flexible and discretionary payments, which supports the idea that mergers lead to less stable and more performance-based remuneration. H1d support is partially supported. While the basic wage is falling, total gross monthly earnings are not clearly falling, as bonuses compensate for lower fixed salaries. As a result, total revenues remain relatively stable in nominal terms, but revenues become more variable and unpredictable. Other results reinforce these findings. Higher concentrations are associated with more overtime and a higher proportion of part-time work, implying greater work intensity and more flexible (and potentially less safe) working arrangements. In short, corporate consolidation does not merely lower wages; it reshapes the wage structure by reducing fixed wages, increasing the reliance on variable compensation, and promoting more flexible work patterns.

5. Discussion

This study examined how corporate concentration, measured using the Herfindahl–Hirschman Index (HHI), is associated with wage formation, compensation structure, working-time arrangements, and selected indicators of job quality in Hungary’s food manufacturing industry between 1993 and 2022. While the HHI captures product market concentration, the observed labour market effects are interpreted through the lens of monopsony theory, which links product market dominance to employer bargaining power (Berger et al., 2022; Rinz, 2022).

The findings reveal a systematic pattern: higher levels of concentration are associated with weaker base wage performance, intensified labour utilisation, and a restructuring of income composition toward bonus-based remuneration.

5.1. Corporate Concentration and Wage Compression

The two-way fixed-effects estimates (Table 9) indicate a statistically significant negative association between concentration and both base hourly wages and gross monthly earnings. The magnitude of the coefficient implies that a 1000-point increase in HHI is associated with an approximately 10.6 percent decline in base wages.

This pattern is consistent with monopsony-based models of labour market power, which predict that firms operating in concentrated environments can sustain wages below competitive benchmarks due to limited worker mobility and reduced outside options (Berger et al., 2022; Rinz, 2022; Schiavone, 2023). Empirical evidence further suggests that labour market concentration contributes to declining labour shares and slower wage growth across industries (Bakir et al., 2021; Izumi et al., 2023).

Importantly, wage compression in this context does not necessarily imply dramatic nominal wage cuts. Rather, it reflects a structural weakening of the role of base wages in overall income determination. This interpretation aligns with findings that corporate concentration reshapes compensation frameworks and affects income distribution without always producing immediate nominal wage reductions (Kristal, 2013; Qiu & Sojourner, 2023).

5.2. Restructuring of Compensation: The Rise of Bonus-Based Income

A central empirical finding concerns the dominant role of regular bonuses in determining gross monthly earnings across subsectors. In several subsectors, base wages measured on an hourly basis exhibit limited explanatory power, while regular bonuses, typically recorded on a monthly basis, account for a substantial share of earnings variation.

This pattern should be interpreted with consideration of differences in measurement units. Nevertheless, the results point to a restructuring of the compensation architecture rather than a simple reduction in total income. Firms operating in concentrated markets appear to rely increasingly on structured and performance-related pay components, a trend documented in the broader literature on changing compensation systems (Kristal, 2013; Sheikh et al., 2018; Yoshikawa et al., 2010). Such arrangements enable firms to link compensation to productivity or firm-level performance metrics while maintaining greater managerial discretion (Qiu & Sojourner, 2023).

The institutional background of Hungary should be taken into consideration while interpreting these results. Hungary’s economy is distinguished by more decentralized wage-setting structures and somewhat less collective bargaining coverage when compared to Western European countries. The power of dominant enterprises to affect wage structures and working conditions may be strengthened by this institutional context (Van Zuilekom & Morrison, 2013). Additionally, the prevalence of foreign-owned businesses and their integration into international production networks may strengthen management control over compensation schemes, especially when it comes to flexible work schedules and performance-based rewards (Diprima, 2023).

The Hungarian case extends this literature to a post-transition context, where weakened collective bargaining institutions and decentralised wage-setting may amplify employer discretion (Bakir et al., 2021; Csaba, 2022). In such environments, concentration may reinforce firms’ ability to reshape wage composition without formally reducing total earnings.

The unstable or negative role of non-regular bonuses in some subsectors further suggests that income variability may reflect fluctuations in working-time arrangements and labour demand. Income volatility has been identified as a key dimension of declining job quality and financial insecurity in concentrated labour markets (LeBaron, 2020; Zhou, 2024).

5.3. Labour Utilisation and Employment Structure

The positive association between concentration and overtime hours (Table 10) indicates intensified labour utilisation in more concentrated subsectors. Rather than expanding employment, dominant firms may adjust output through longer working hours for existing employees. Similar patterns have been documented in contexts where labour market power strengthens employer discretion in allocating work intensity (Berger et al., 2022; T. Liu et al., 2025).

From a cost-minimisation perspective, increasing overtime may be administratively simpler than hiring and training additional workers (Tuckman, 2005). However, sustained reliance on overtime can also reflect asymmetric bargaining power in monopsonistic labour markets (Brennan, 2016).

The positive relationship between HHI and part-time employment (Table 11) further suggests greater reliance on flexible or non-standard employment arrangements. Previous research indicates that concentrated firms may expand non-standard contracts as a mechanism of labour cost containment and risk transfer (Benton & Kim, 2022; T. Liu et al., 2025). The Hungarian evidence is consistent with this interpretation, indicating structural variation in employment composition across levels of market concentration.

5.4. Paid Leave and Job Quality

The negative association between concentration and paid leave (Table 10) points toward potential weakening of non-wage employment protections in highly concentrated environments. Paid leave serves as an indicator of institutionalised worker protections and job quality. Prior research suggests that employer market power may extend beyond wage-setting to broader employment standards and non-wage benefits (Clapp, 2021; Passerini, 2025).

In post-transition economies characterised by decentralised wage bargaining and declining union density (Csaba, 2022), concentration may reinforce existing asymmetries in labour market power. The Hungarian case illustrates how concentrated market structures may influence both monetary and non-monetary dimensions of employment.

5.5. Mechanisms and Mediation Effects

The combined earnings model (

Table 13. Combined Earnings Model.

Dependent Variable	Coefficient (HHI)	Robust SE	t-Value	p-Value	Significance
Base Hourly Wage (H1a)	−0.000278	0.000055	−5.021	0.000003	Significant
Regular Bonuses (H1b)	0.005599	0.002484	2.254	0.028	Significant
Non-Regular Bonuses (H1c)	0.122538	0.023415	5.233	0.000001	Significant
Gross Monthly Earnings (H1d)	−0.003662	0.004867	−0.752	0.454	Not significant
Overtime Hours (H2)	0.004551	0.001946	2.338	0.022	Significant
Share of Part-time Employment (H3)	0.00001006	0.0000028	3.578	0.001	Significant

) indicates that once working-time variables and compensation components are included, the direct effect of concentration on earnings becomes statistically insignificant. This suggests that concentration influences income partly through indirect channels, specifically, through adjustments in compensation composition and employment arrangements.

Such mechanisms are consistent with research indicating that corporate concentration reshapes income structures and labour cost allocation strategies rather than solely suppressing wages directly (Bakir et al., 2021; T. Liu et al., 2025; Qiu & Sojourner, 2023). Concentration may therefore operate by reallocating bargaining power and altering the institutional architecture of compensation.

These findings should be interpreted in light of Hungary’s institutional labour market framework. While part-time employment remains less prevalent compared to Western European economies, regulatory changes over the past decades have increased labour market flexibility and employer discretion. Hungary operates within the framework of the European Union’s Working Time Directive, which sets limits on weekly working hours and minimum rest periods; however, the implementation of these regulations allows for significant variation in working-time arrangements and overtime practices. In addition, overtime compensation and working-time flexibility are often shaped by firm-level agreements, which may reinforce employer bargaining power in more concentrated sectors.

Overall, the Hungarian evidence supports the interpretation that corporate concentration restructures labour relations by strengthening employer discretion in wage-setting, working-time allocation, and employment composition. Rather than eliminating income, concentrated market structures appear to reconfigure the mechanisms through which income is generated and distributed.

The study’s conclusions are especially pertinent to Hungary’s institutional framework, where collective bargaining and labour market regulation are still comparatively inadequate by Western European standards. Growing corporate concentration may have more noticeable implications on non-wage labour conditions and pay structures in certain situations. This implies that labour market policies that increase worker rights and institutional negotiating frameworks should be implemented in addition to competitiveness policy in Hungary and other transition countries.

6. Conclusions

This study provides long-term empirical evidence on the relationship between corporate concentration and labour market outcomes in Hungary’s food manufacturing industry between 1993 and 2022. Using industry-level panel data and two-way fixed-effects models, the analysis demonstrates that higher levels of product market concentration are systematically associated with lower base wages, greater overtime intensity, reduced paid leave, and a higher prevalence of part-time employment.

The panel regression results provide direct quantitative evidence that higher levels of corporate concentration are associated with lower base wages, reduced earnings, intensified overtime, fewer paid holidays, and a greater reliance on part-time employment. Importantly, the combined model suggests that the wage effects of concentration operate partly through structural adjustments in working conditions and compensation composition. These findings reinforce the interpretation that corporate concentration in Hungary’s food industry reshapes labour relations not only through direct wage suppression but also through institutional and organizational restructuring of employment conditions.

Importantly, the findings indicate that corporate concentration does not necessarily reduce nominal earnings outright. Instead, it reshapes the structure of compensation. The weakening role of base wages and the increasing reliance on regular bonuses suggest a transformation in income determination mechanisms, with greater managerial discretion over compensation components.

The combined model further indicates that the association between concentration and earnings operates partly through adjustments in working-time arrangements and employment composition. These results are consistent with monopsony-based interpretations of employer market power in concentrated industries.

From a policy perspective, the findings underscore the importance of integrating labour market considerations into competition policy assessments. In sectors characterized by high concentration, regulatory frameworks should account not only for price effects but also for wage dynamics, employment structures, and non-wage working conditions. Strengthening collective bargaining institutions and reinforcing the protection of non-wage employment rights may help mitigate the labour market consequences of rising corporate concentration.

Overall, the Hungarian case illustrates how product market concentration can extend beyond pricing power and influence the internal architecture of employment relations in transition economies.

7. Limitations and Future Research

This study has several limitations. First, the available dataset covers the period up to 2022, reflecting the standard time lag in the availability of harmonised industry-level data. While extending the analysis to include more recent years may be desirable in future research, the current time span already provides a sufficiently long-term perspective to capture structural trends. Additionally, the initial objective was to begin the analysis in the late socialist period (1980s); however, pre-transition data were not sufficiently harmonised with post-transition statistical classifications to ensure consistent longitudinal comparison.

The analysis does not directly assess the stationarity of the variables. However, because fixed-effects panel models were used and the focus was on conditional associations instead of long-run equilibrium relationships, the estimates should be taken with a grain of salt. Non-stationarity and common trends may influence coefficient magnitudes, and subsequent research could remedy this by employing formal panel unit root and cointegration tests.

Second, the analysis is based on industry-level data rather than firm-level or individual-level microdata. Although this approach captures structural patterns of concentration, it limits the ability to examine heterogeneity in income, working hours, and contractual arrangements. Third, working-time dynamics are inferred indirectly through compensation structures and are not directly modelled within the regression framework. Finally, the findings are specific to Hungary’s food industry and may not be fully generalisable to other sectors or institutional contexts.

The study’s conclusions are especially pertinent to Hungary’s institutional framework, where collective bargaining and labour market regulation are still comparatively inadequate by Western European standards. Growing corporate concentration may have more noticeable effects on non-wage working conditions and wage structures in these situations. This implies that labour market policies that strengthen worker protections and institutional bargaining frameworks should be implemented in addition to competition policy in Hungary and other transition economies.

These limitations suggest several directions for future research. Further work could explore sectoral heterogeneity within Hungary by analysing less concentrated food subsectors. Comparing highly concentrated and less concentrated industries would provide deeper insight into the relationship between concentration and labour market outcomes. In addition, the use of firm-level or matched employer–employee microdata would allow for more precise identification of the microeconomic mechanisms linking concentration to wages, working hours, and employment security, including intra-firm wage dispersion and contractual heterogeneity.

Future research could also incorporate data from the late socialist period to provide a longer historical perspective and enable comparison between pre- and post-transition labour market structures. Cross-country comparative studies could examine whether the patterns observed in Hungary are characteristic of other post-transition economies in Central and Eastern Europe, and also whether they differ from those in Western European institutional contexts.

Complementary qualitative and quantitative studies focusing on workplace governance, managerial decision-making, and collective bargaining practices would further enhance understanding of how corporate concentration restructures employment relations in practice. Such analyses would help clarify the role of institutional environments in shaping the labour market effects of corporate concentration.