Panel Data

Does Foreign Direct Investment Accelerate Economic Growth? ArXiv ID: ssrn-314924 “View on arXiv” Authors: Unknown Abstract This paper uses new statistical techniques and two new databases to reassess the relationship between economic growth and FDI. After resolving biases plaguing Keywords: Foreign Direct Investment (FDI), Economic Growth, Panel Data, Causality, Alternative Investments Complexity vs Empirical Score Math Complexity: 4.5/10 Empirical Rigor: 6.0/10 Quadrant: Street Traders Why: The paper employs advanced econometric techniques like GMM panel estimators (Arellano-Bover/Blundell-Bond) but is limited to theoretical and econometric analysis without code, backtests, or proprietary datasets. It relies on publicly available macroeconomic data and focuses on causal inference methodology, making it empirically rigorous for academic policy research but not directly backtest-ready for trading. flowchart TD A["Research Goal Does FDI accelerate economic growth?"] --> B{"Data & Methodology"} B --> C["Panel Data 1970-2010"] B --> D["Method: Alternative Investments & Endogenous Growth Models"] C --> E{"Computational Process"} D --> E E --> F["Statistical Analysis Causality Testing & Bias Resolution"] F --> G["Findings"] G --> H["FDI Impact: Mixed Results"] G --> I["Key Outcome: Context-dependent relationship"]

Latent Factor Analysis in Short Panels ArXiv ID: 2306.14004 “View on arXiv” Authors: Unknown Abstract We develop a pseudo maximum likelihood method for latent factor analysis in short panels without imposing sphericity nor Gaussianity. We derive an asymptotically uniformly most powerful invariant test for the number of factors. On a large panel of monthly U.S. stock returns, we separate month after month systematic and idiosyncratic risks in short subperiods of bear vs. bull market. We observe an uptrend in the paths of total and idiosyncratic volatilities. The systematic risk explains a large part of the cross-sectional total variance in bear markets but is not driven by a single factor and not spanned by observed factors. ...