The Two-Stage Least Squares (2-SLS) is a well known econometric technique used to estimate the parameters of a multi-equation (or simultaneous equations) econometric model when errors across the equations are not correlated and the equation(s) concerned is (are) over-identified or exactly...

This paper builds on Kocenda (2001) and extends it in two ways. First, two new intervals of the proximity parameter ε (over which the correlation integral is calculated) are specified. For these ε-ranges new critical values for various lengths of the data sets are introduced and through Monte...

The pandemic and the war in Ukraine are prompting many to ask whether old macroeconomics still apply? DePillis (2022) notes that profits and inflation are highly correlated, but the direction and strength of the causal path linking them is unknown. This paper briefly describes new causal path...

This paper studies the relationship between lobbying, free emission allowance allocation and firm outcomes in the European Union Emissions Trading System (ETS). I draw on administrative data from the EU Transpareny Register (TR) and the European Union Transaction Log (EUTL), and construct a...

GLOBAL FINANCE LIQUIDITY RISK REVISITED: Development of A Framework for Liquidity Assessment in Portfolio Construction Process: Presentations to the JP Morgan Global Head of Quant Research & Analytics and US Head of Portfolio Construction Teams:Presentations To: JP Morgan Global Head of Quant...

GLOBAL FINANCE LIQUIDITY RISK REVISITED: JP Morgan Alternative Assets Portfolio Liquidity Assessment Framework & Models: $500 Billion Fund of Funds: 17 Asset ClassesPresentations atJP Morgan World HQ, 270 Park Ave, Manhattan, NY, USAToJP Morgan Global Head of Quant Research & Analytics, JP...

The COVID-19 pandemic has increased the need for timely and granular information to assess the state of the economy in real time. Weekly and daily indices have been constructed using higher frequency data to address this need. Yet the seasonal and calendar adjustment of the underlying time...

We introduce the package ddml for Double/Debiased Machine Learning (DDML) in Stata. Estimators of causal parameters for five different econometric models are supported, allowing for flexible estimation of causal effects of endogenous variables in settings with unknown functional forms and/or...

We introduce the package ddml for Double/Debiased Machine Learning (DDML) in Stata. Estimators of causal parameters for five different econometric models are supported, allowing for flexible estimation of causal effects of endogenous variables in settings with unknown functional forms and/or...

This paper demonstrates that if we intend to optimally rank order n objects (candidates) each of which has m attributes or rank scores awarded by m evaluators, then the ordinal ranking of objects by the conventional principal component based factor scores turns out to be suboptimal. Three...