Super-linear Scaling Behavior for Electric Vehicle Chargers and Road Map to Addressing the Infrastructure Gap

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1. Apparenté Pas pertinent

   Deep Learning Macroeconomics

   Rafael R. S. Guimaraes · 2022 · Économétrie · Résumé IA disponible

   Résumé scientifique

   Limited datasets and complex nonlinear relationships are among the challenges that may emerge when applying econometrics to macroeconomic problems. This research proposes deep learning as an approach to transfer learning in the former case and to map relationships between variables in the latter case. Although macroeconomists already apply transfer learning when assuming a given a priori distribution in a Bayesian context, estimating a structural VAR with signal restriction and calibrating parameters based on results observed in other models, to name a few examples, advance in a more systematic transfer learning strategy in applied macroeconomics is the innovation we are introducing. We expl…

2. Apparenté Pas pertinent

   A Descriptive Method of Firm Size Transition Dynamics Using Markov Chain

   Boyang You, Kerry Papps · 2022 · Économétrie · Résumé IA disponible

   Résumé scientifique

   Social employment, which is mostly carried by firms of different types, determines the prosperity and stability of a country. As time passing, the fluctuations of firm employment can reflect the process of creating or destroying jobs. Therefore, it is instructive to investigate the firm employment (size) dynamics. Drawing on the firm-level panel data extracted from the Chinese Industrial Enterprises Database 1998-2013, this paper proposes a Markov-chain-based descriptive approach to clearly demonstrate the firm size transfer dynamics between different size categories. With this method, any firm size transition path in a short time period can be intuitively demonstrated. Furthermore, by utili…

3. Apparenté Pas pertinent

   Digital Divide: Empirical Study of CIUS 2020

   Joann Jasiak, Peter MacKenzie, Purevdorj Tuvaandorj · 2023 · Économétrie · Résumé IA disponible

   Résumé scientifique

   Canada and other major countries are investigating the implementation of ``digital money'' or Central Bank Digital Currencies, necessitating answers to key questions about how demographic and geographic factors influence the population's digital literacy. This paper uses the Canadian Internet Use Survey (CIUS) 2020 and survey versions of Lasso inference methods to assess the digital divide in Canada and determine the relevant factors that influence it. We find that a significant divide in the use of digital technologies, e.g., online banking and virtual wallet, continues to exist across different demographic and geographic categories. We also create a digital divide score that measures the s…

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   A multi-cell experimental design to recover policy relevant treatment effects, with an application to online advertising

   Caio Waisman, Brett R. Gordon · 2023 · Économétrie · Résumé IA disponible

   Résumé scientifique

   Experiments are an important tool to measure the impacts of interventions. However, in experimental settings with one-sided noncompliance, extant empirical approaches may not produce the estimates a decision-maker needs to solve their problem. For example, these experimental designs are common in digital advertising settings, but they are uninformative of decisions regarding the intensive margin -- how much should be spent or how many consumers should be reached with a campaign. We propose a solution that combines a novel multi-cell experimental design with modern estimation techniques that enables decision-makers to recover enough information to solve problems with an intensive margin. Our …

5. Apparenté Pas pertinent

   Econometric Inference with Machine-Learned Proxies: Partial Identification via Data Combination

   Lixiong Li · 2026 · Économétrie · Résumé IA disponible

   Résumé scientifique

   Empirical researchers increasingly use upstream machine-learning (ML) methods to construct proxies for latent target variables from complex, unstructured data. A naive plug-in use of such proxies in downstream econometric models, however, can lead to biased estimation and invalid inference. This paper develops a framework for partial identification and inference in general moment models with ML-generated proxies. Our approach does not require restrictive assumptions on the upstream ML procedure, such as consistency or known convergence rates, nor does it require a complete validation sample containing all variables used in the downstream analysis. Instead, we assume access to two datasets: a…

6. Apparenté Pas pertinent

   Machine Learning Estimation of Heterogeneous Treatment Effects with Instruments

   Vasilis Syrgkanis, Victor Lei, Miruna Oprescu et al. · 2019 · Économétrie · Résumé IA disponible

   Résumé scientifique

   We consider the estimation of heterogeneous treatment effects with arbitrary machine learning methods in the presence of unobserved confounders with the aid of a valid instrument. Such settings arise in A/B tests with an intent-to-treat structure, where the experimenter randomizes over which user will receive a recommendation to take an action, and we are interested in the effect of the downstream action. We develop a statistical learning approach to the estimation of heterogeneous effects, reducing the problem to the minimization of an appropriate loss function that depends on a set of auxiliary models (each corresponding to a separate prediction task). The reduction enables the use of all …

7. Apparenté Pas pertinent

   Adaptive Pricing in Insurance: Generalized Linear Models and Gaussian Process Regression Approaches

   Yuqing Zhang, Neil Walton · 2019 · Économétrie · Résumé IA disponible

   Résumé scientifique

   We study the application of dynamic pricing to insurance. We view this as an online revenue management problem where the insurance company looks to set prices to optimize the long-run revenue from selling a new insurance product. We develop two pricing models: an adaptive Generalized Linear Model (GLM) and an adaptive Gaussian Process (GP) regression model. Both balance between exploration, where we choose prices in order to learn the distribution of demands & claims for the insurance product, and exploitation, where we myopically choose the best price from the information gathered so far. The performance of the pricing policies is measured in terms of regret: the expected revenue loss cause…

8. Apparenté Pas pertinent

   Understanding Volatility Spillover Relationship Among G7 Nations And India During Covid-19

   Avik Das, Dr. Devanjali Nandi Das · 2022 · International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.10, Issue 6, pp.c261-c269, June 2022 · Résumé IA disponible

   Résumé scientifique

   Purpose: In the context of a COVID pandemic in 2020-21, this paper attempts to capture the interconnectedness and volatility transmission dynamics. The nature of change in volatility spillover effects and time-varying conditional correlation among the G7 countries and India is investigated. Methodology: To assess the volatility spillover effects, the bivariate BEKK and t- DCC (1,1) GARCH (1,1) models have been used. Our research shows how the dynamics of volatility spillover between India and the G7 countries shift before and during COVID-19. Findings: The findings reveal that the extent of volatility spillover has altered during COVID compared to the pre-COVID environment. During this pande…