Econometrics Commons^™

Essays On Futures Market And Machine Learning, Jonathan J. Lopez Camara

Dissertations, Theses, and Capstone Projects

Chapter 1 - Big Data And Machine Learning To Predict Overnight Interest Rates. This paper is a brief introduction to the two main pieces I have elaborated as part of the dissertation. Here, I explain the reasons why I have done my research about predicting the overnight interest rates for Mexico and the United States using big data and machine learning models. I explain the connection between the two research papers, I define some basic concepts such as future contracts and the overnight funding rate for Mexico. There is a summary about the data I use, and the machine learning …

Big Data And Inflation Forecasting In Nigeria: A Text Mining Application., M. A. Adebiyi, A. O. Adenuga, T. S. Olusegun, O. O. Mbutor

Economic and Financial Review

The success of monetary policy is substantially predicated on the availability of reliable forecast of inflation. However, the shocks arising from COVID-19 and the Russia-Ukraine war have brought about significant economic uncertainties; thus, necessitating the fine-tuning of existing forecasting models of the Central Bank of Nigeria. This study explores the usefulness of public sentiments obtained using machine learning methods to improve the predictive power of the existing short-term inflation forecasting model (STIF) in Nigeria. Findings indicate that, for all components of inflation, models that include the computed sentiment index perform better in both in-sample and out-sample forecasts than those excluding …

Essays In Empirical Economics, Agustin Indaco

Dissertations, Theses, and Capstone Projects

This dissertation consists of two chapters that utilize distinct econometric methods and novel datasets.

In the first chapter, “From Twitter to GDP: Estimating Economic Activity From Social Media”, I collect all geo-located image tweets shared on Twitter in 2012-2013 to study whether the volume of tweets is a valid proxy for estimating current GDP in USD at the country level. My preferred model explains 94 percent of the cross-country variation and the residuals from the model are negatively correlated to a data quality index, indicating that my estimates of GDP are more accurate for countries with more reliable GDP data. …

The Paradox Of Big Data, Gary N. Smith

Pomona Economics

Data-mining is often used to discover patterns in Big Data. It is tempting believe that because an unearthed pattern is unusual it must be meaningful, but patterns are inevitable in Big Data and usually meaningless. The paradox of Big Data is that data mining is most seductive when there are a large number of variables, but a large number of variables exacerbates the perils of data mining.

Rhode Island Current Conditions Index — September 2011, Leonard Lardaro

The Rhode Island Current Conditions Index

No abstract provided.