What drives German foreign direct investment? New evidence using Bayesian statistical techniques

Camarero, Mariam; Montolio, Laura; Tamarit, Cecilio

doi:10.1016/j.econmod.2019.08.017

Cited by 22 publications

(26 citation statements)

References 66 publications

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“…We used the dataset applied in Camarero et al (2019b) for the selection of the main determinants of German outward FDI stock using a Bayesian Model Averaging (BMA) approach, which included data for 59 destination countries (38 developed and 21 developing ones) and covered the period 1996-2012. 4 For our purpose, we restricted the sample to Latin American and Asian countries.…”

Section: Methodology and Datamentioning

confidence: 99%

“…Their FDI data were obtained from the UNCTAD's Bilateral FDI Statistics. 5 The explanatory variables that we included were those selected (see Camarero et al (2019b)) as robust FDI determinants in the BMA analysis for these country-groups. A list of the considered variables and sources is provided in Table A1, whereas Table A2 reports the descriptive statistics for each country-group.…”

Section: Methodology and Datamentioning

confidence: 99%

“…Their findings showed that large markets, macroeconomic stability, and institutional factors were key variables for explaining German FDI in Latin American countries, while for Asian countries, established trade relations, openness, high labor productivity, big market size, as well as low telecommunications infrastructure were key for FDI attraction. Similarly, the work in Camarero et al (2019b), using a different Markov chain Monte Carlo (MCMC) method for the Bayesian analysis, concluded that even though the size of the market was key for FDI in both Latin American and Asian countries, also vertical FDI prevailed in Asian countries, whereas the quality of institutions was key for German investment in Latin America.…”

Section: Related Literaturementioning

confidence: 99%

See 2 more Smart Citations

Understanding German FDI in Latin America and Asia: A Comparison of GLM Estimators

2020

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The growth of Foreign Direct Investment (FDI) in developing countries over the last decade has attracted an intense academic and policy-oriented interest for its determinants. Despite the gravity model being considered a useful tool to approximate bilateral FDI flows, the literature has seen a growing debate in relation to its econometric specification, so that which is the best estimator for the gravity equation is far from conclusive. This paper examines the determinants of German outward FDI in Latin America and Asia for the period 1996-2012 by evaluating the performance of alternative Generalized Linear Model (GLM) estimators. Our findings indicate that Negative Binomial Pseudo Maximum Likelihood (NBPML) is the estimator best matched to our data, followed by Gamma Pseudo Maximum Likelihood (GPML). Furthermore, German FDI in Latin America is found to be predominantly vertical in nature, whereas that in Asia is mainly market-seeking.

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Section: Methodology and Datamentioning

confidence: 99%

Section: Methodology and Datamentioning

confidence: 99%

Section: Related Literaturementioning

confidence: 99%

See 1 more Smart Citation

Understanding German FDI in Latin America and Asia: A Comparison of GLM Estimators

2020

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“…A larger market offers a better opportunity for the large-scale foreign investors, facilitating the sales not only on the internal market, but also on other markets. In their paper, Camarero, Montolio, and Tamarit analyzed the determinants of German stock outward FDI and find that determinants associated with horizontal FDI appear to be dominant for explaining FDI in developed countries while for the group of developing countries covariates associated with vertical FDI motives play a larger role [22]. Nakamura and Zhang considered models that describe foreign firms' and host countries' decisions on foreign direct investment (FDI) when host country product markets are characterized by certain types of market structures.…”

Section: Foreign Direct Investments (Fdi) In the Chemical Industrymentioning

confidence: 99%

“…The data collection was performed in June 2019. The list of the 150 foreign companies from the chemical industry was obtained from The National Trade Register Office and contained the names and the addresses of the foreign companies already established on the Romanian market, as FDI, before 2018 and functioning in 2018 in the chemical industry (19)(20)(21)(22), with more than 100 employees and a capital with more than 50% as foreign contribution.…”

Section: Data Collection and Sampling Designmentioning

confidence: 99%

The Profile of the Foreign Investor in the Romanian Chemical Industry

2020

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The main aim of this study is to build the investor’s profile in the Romanian chemical industry and to highlight the factors that influenced the decision of investing in Romania rather than other Central Eastern European countries. The data collection was performed in June 2019 and the list of the 150 foreign companies from the chemical industry was obtained from The National Trade Register Office. Data used in this research were collected using a questionnaire. Dependent variable represents the probability of investing in Romania, with the option of the other Central and Eastern European countries as reference group. The main part of our analysis focus on this question: “Which were the reasons that made you decide invest in Romania?” For analysis, a number of six main classes are used: Infrastructure, labor force, Agglomeration factors, Knowledge, Market Size and Cost factors (as independent variables). Main results consist in the presence of three factors with a positive impact. The paper also highlights that the main advantage considered by a foreign investor in Romania is represented by the cheap labor force. As a secondary conclusion, companies are also interested in other factors that are mentioned in the paper.

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Financing sustainable development goals in Sub‐Saharan Africa: Does international capital flows matter?

Slimani,

Omri,

Abbassi

2024

Sustainable Development

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This study investigates the role of international capital flows in financing the Sustainable Development Goals (SDGs) in Sub‐Saharan Africa (SSA). Using data from 41 SSA countries from 2000 to 2018 and employing the System Generalized Method of Moments (System GMM), the research examines the impact of Foreign Direct Investment (FDI) and remittances on the SDGs across disaggregated levels (economic, social, and environmental sustainability) and the aggregated level (SDGI). The findings underscore the crucial significance of international capital flows as essential financing sources for SSA countries. FDI emerges as a contributor to economic and social sustainability at the disaggregated level, yet it exhibits negative effects on environmental sustainability. Conversely, remittances are shown to positively contribute to economic and social sustainability at the disaggregated level. However, the impact of international capital flows on the aggregate SDGI is found to be insignificantly positive. These results highlight the necessity for policymakers in SSA to devise strategies that maximize the benefits of FDI while addressing its adverse effects on environmental sustainability. Furthermore, they emphasize the importance of strengthening policies aimed at directing remittances towards sustainable investments, thereby advancing the achievement of the SDGs. Governments are urged to prioritize enhancing regulatory capacities in environmental matters through investments in modern technologies and appropriate standards, aiming to strike a balance between environmental protection and economic needs. Additionally, they should prioritize transparency, public participation, and robust enforcement mechanisms. Encouraging environmentally friendly foreign investments and promoting regional and international cooperation are also crucial steps towards effectively managing local environmental challenges.

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What drives German foreign direct investment? New evidence using Bayesian statistical techniques

Cited by 22 publications

References 66 publications

Understanding German FDI in Latin America and Asia: A Comparison of GLM Estimators

Understanding German FDI in Latin America and Asia: A Comparison of GLM Estimators

The Profile of the Foreign Investor in the Romanian Chemical Industry

Financing sustainable development goals in Sub‐Saharan Africa: Does international capital flows matter?

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