Foreign Direct Investment (FDI) is seen as a significant driver of economic growth and a potential ally in the struggle against poverty and inequality, making emerging countries focus on attracting this type of investment. Thus, understanding factors that impact the concentration of regional FDI is essential to verifying which characteristics encourage or deter foreign investment. Likewise, the literature has explored institutional factors such as corruption as determining factors for the concentration of FDI. Within this framework, this study aims to empirically examine the sensitivity of multinational enterprises (MNEs) to corruption. Few studies have been carried out on this subject, mainly in Latin American economies. We employ a unique Brazilian municipality-level FDI database to investigate whether corruption hinders (i.e., corruption acting as “sand”) or promotes the concentration of foreign investment (i.e., corruption acting like “grease”). Additionally, we believe that analyzing different economic sectors is essential to deepening the knowledge about the impacts of corruption on FDI. Our results show that corruption acts as “grease” for both overall FDI and at the level of individual sectors. Finally, when taking a non-linear approach, our findings show that corruption acts as grease for FDI only in regions with intermediate (medium–low) levels of corruption.

This study proposed to explore real estate trends in the high-rise housing market in Belém, Northern Brazil. We based the theoretical approach on the macroeconomic, territorial, and social elements of the high-rise segment both in national and international contexts. The sample comprised 137 high-rise projects launched throughout the 2005–2017 period. A quadratic regression model confirmed real estate susceptibility to macroeconomic oscillation. A geographically weighted regression model revealed that larger dwellings were launched more in upper-income, lower formal employment rate, and lower infrastructure coverage regions of Belém. A multinomial logit regression model established differences in the launching likelihood between different categories of housing size projects. The outcomes were compared with worldwide tendencies, seeking both common and unique patterns of real estate exploitation. The methodological forms of exploring real estate trends in developing countries—which are scarcer—add significant scientific value for the urban planning community, as they assist public policy by identifying the susceptibility of urban areas to land exploitation, in addition to enabling replication of such real estate diagnostics in other cities of emerging countries.

Purpose: Our study seeks to measure the impact of Foreign Direct Investments (FDI) in the services sector on the productivity of municipalities in the state of São Paulo. Theoretical framework: FDI in the services sector has become increasingly important for emerging economies due to the spillover effects, which can boost regional economic development. Methodology/Approach: This study uses econometric modeling to measure the impact of services FDI at the municipal level in the state of São Paulo, the most FDI-intensive region in Brazil. To do so, this study employs an unbalanced panel of data that includes all FDI-receiving municipalities in the state between 2010 and 2016. Findings: Our results point to a positive relationship between FDI in services sectors and municipal productivity. Research, practical & social implications: This study outcomes offer valuable perspectives for the formulation of public policies aimed at attracting foreign investments. They also have important implications for the service sector and could be a reference for future studies on the subject. Originality/ Value: This study addresses FDI in emerging countries, an important discussion given the impact of this type of investment on economic development and social indicators. In addition, this paper expands the FDI literature beyond the manufacturing sector. Keywords: Foreign Direct Investment; Foreign Direct Investment in Services; Spillovers; Productivity.