The purpose of the thesis is to analyze how the automotive manufacturing companies being active in Hungary operate in global value chains, with a particular focus on suppliers. Although the topic of GVC is widespread and discussed in international literature, there is a gap in relation to the Hungarian automotive manufacturing industry, especially in the current situation when the COVID-19 pandemic affects the operation of the multinational enterprises. The main identified research question is the following: What is the value creation of the automotive manufacturing industry in Hungary within global value chain? The research process started with a comprehensive literature review and theoretical background analysis about the GVC concept (including the introduction of ‘Smile-curve’) and FDI investment in Central and Eastern Europe (including the characterization of near-shoring activities) and continued with conducting a sample survey and semi-structured interviews with the key car parts suppliers. Executive board, managerial level and engineers were the target persons both for the survey and for interviews. Based on the literature review, I formulated two hypotheses: 1. The theory of ‘Smile curve’ is also valid in case of the Hungarian automotive manufacturing industry, typically low value-added production processes take place in the country. 2. In addition to the central location, the cheap and skilled Hungarian labour was the most important factor in the near-shoring activities of multinational companies expanding to Hungary. In order to be able to accept or reject the first hypothesis about the relevance of the so called ‘Smile curve’ in the Hungarian automotive manufacturing industry, to define position of the automotive manufacturer companies being active in Hungary in the global automotive manufacturing value chain and to create an in-depth understanding about investment incentives of the Western European firms in the country, I prepared an online survey. To test my second hypothesis about the reasons of near-shoring activity in Hungary, I conducted 3 interviews with industry experts from TIER 1 companies of different size. The targeted automotive parts manufacturers are all suppliers of the 5 OEMs present in Hungary (Audi, BMW, Mercedes, Opel and Suzuki) among others. The new results of the doctoral dissertation are the following: I can reject the first hypothesis about the relevance of ‘Smile curve’ in the Hungarian automotive manufacturing industry, because beside manufacturing activities with low added value typically, also research and development activities take place at bigger multinational companies with higher added value. I can accept the second hypothesis about near-shoring in Hungary, because beside the ‘proximity to export markets’, the cheap but skilled labour was decisive when multinationals decided to invest in the country. The ‘positive support system’, ‘favourable tax conditions’, ‘government policy’ and ‘proximity to HQ’ were aspects that companies used, but they are rather neutral factors. The ‘good infrastructure’ is not so good in the real life and the ‘cheap raw material’ is not cheap, because firms have to deal with world market prices, thus, these were not attractive to investors. Further results about the business operations of the analyzed supplier companies: The purchasing decisions for the Hungarian production happens locally decisively, either independently or with involving the headquarter. The manufactured products are typically drive chains, body parts and electric sensors and the proportion of products designated by OEMs is rather high. Western Europe is the biggest export market of the companies analysed, followed by China, North-America and the Central Eastern European region. Relocation processes are not characteristic of the firms. If so, only from other country to Hungary and it is also determined by OEMs providing new opportunities for them. In some cases, wage costs and logistics also play a role in the relocation process. Electromobility and autonomous driving are the most affecting trends in the automotive manufacturing industry. The semiconductor shortage as a serious downside risk is also the result of the pandemic. The effects of COVID-19 are becoming less pronounced today, but the semiconductor crisis is continuing. Favourable tax conditions and higher value added are the success criteria that will help the Hungarian automotive manufacturing industry to remain competitive in the future. Professional trainings, more support for SMEs and favourable legal conditions are also important aspects. Today, the CEE region, including Hungary is a net exporter of knowledge-intensive goods. To improve its global competitiveness and to be able to move into higher-value-added goods and services, the region should invest more in R&D, infrastructure, education and collaboration between companies and universities. The key players in the automotive part manufacturing has realized that value added is a very important factor in the success of an industry and it can be increased due to investment in research and development and innovation. As revealed by the research, they have already established R&D centers and joint projects with universities (e.g. departments), so companies are well on their way to producing higher added value.
In our research, we aim to shed light on the role of overdue debt in reinforcing poverty. This not only helps to better understand the dynamics of poverty trap induced by overdue debt but also enhances the rediscussing of current policy tools. Our research is based on data collected with targeted questionnaires in March and April 2019 by the Soreco Research Kft. Data were recorded with a personal question and answer method, by a so-called multi-stage stratified random sampling procedure. The data collection was anonymised and focused on the financial and liquidity decisions of households in small settlements in one of the most disadvantaged counties of Hungary, Borsod-Abaúj-Zemplén (BAZ) county. The sample is representative on the level of households living in small settlements. After cleaning the raw data, we have information from 504 households and 1794 individuals. 1196 individuals are of legal age, from whom 179 had overdue debt. We develop a theoretical model inspired by Akerlof (1978), Tirole (2006), and Mukherjee, Subramanian, Tantri (2019) to derive a feasibility condition for market-based debt relief programs. Our empirical analysis aims at investigating the role of overdue debt in creating poverty trap. With the help of statistical analysis and linear probability models we examine the impact of overdue debt on employment, on having a bank account, and on mental- and physical- health based on targeted questionnaires and in-depth interviews in the most disadvantaged regions of Hungary. We controlled for socioeconomic factors (e.g., gender, age, education level, ability to pay) and for settlement and county development indicators. In these regions, a significant part of the society has been the victim of financial exclusion well before the Covid 19 crisis, even under prospering economic conditions. Results: § The theoretical model shows that lenders have no interest to offer payment reductions if non-performing borrowers are few, have small debts, and are difficult to reach. In this situation, poor debtors serve better as deterrents, similarly if we put them into a pillory. § Calibrating model parameters to poor households struggling with overdue debts, we show that this might be the case on our sample, too. § As, in normal economic circumstances, private debt relief programs are typically not feasible, a state subsidy would be needed to consolidate the debts of the poor. State intervention can be justified both by positive externalities and moral considerations. § We find that many borrowers hide from debt collection as a consequence of overdue debt that has escalated to an unbearable level due to penalty rates. These borrowers are following the hiding strategy and take their decisions accordingly: to avoid deductions, they do not apply for registered jobs, do not open bank accounts and consequently, they are forced to live under constant stress. § To sum up the impact of overdue debt on social inclusion factors and according to our estimations, overdue debts reduce the likelihood of having a registered job by nearly 14 percentage points. Not having a registered job reduces the probability of owning a bank account by 22 percentage points and, in addition, overdue debts further decrease the probability by 5 percentage points. In addition, overdue debt also has a negative effect on the health of those living in the same household as the debtor, and this negative effect is greater than what a combined high school diploma and diploma could compensate for (0.4 versus 1.08-0.72 = 0.36). § Overdue debt, therefore, leads to a certain type of debt-trap mechanism resulting in significant loss for both the individual and the society. In this light, policy makers should pay more attention to addressing credit cycles and resolving non-performing debt obligations, especially in this fragile part of the society.