Inflation Impact on Foreign Direct Investment - Evidence from Western Balkan Countries
Bibliographic record
Abstract
The objective of this article is to explore the degree of relationship between inflation and foreign direct investments (FDI) and other macroeconomic indicators in Western Balkan countries.This is a quantitative empirical study relied on regression model, generalized method of moments (GMM) and other econometric measurements such as fixed effects model, random effects model and Pooled OLS model.The data on this empirical study is relied on 15 years observation of each of six Western Balkan countries.The study combines two types of variables with panel data from World Bank Open Data and KAS for the period 2008-2022.The results indicate a significant positive impact of inflation rate on FDI.A percentage rise in inflation rate is related with 0.30% short-term FDI growth, at an average of 5% ceteris paribus.Furthermore, the results indicate the statistically positive effect of inflation rate on GDP growth.A percentage increase in inflation rate is correlated with 0.17% increase in GDP.On the other hand, results revealed the inversely relationship between inflation rate and unemployment.A percentage change in inflation rate is associated by -0.168% reduction of unemployment in the short term.This intercourse will reduce unemployment and may provide conditions for increased employment in these countries.The results of the study confirm that the rate of inflation, FDI, GDP growth and unemployment rate over the years manifest an inelastic relationship among themselves.Based on our study findings we suggest some policy recommendations.Governments, through appropriate fiscal policies, can support local monetary policies to manage inflation.Initially, through policies that will enable the reduction of public expenditures and the reduction of high inflation rates.Secondly, Central banks, through appropriate policies, should manage inflation rates in their countries in order to ensure macroeconomic stability.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".