Results 111 to 120 of about 124,938 (276)

A Fuzzy Framework for Realized Volatility Prediction: Empirical Evidence From Equity Markets

Journal of Forecasting, EarlyView.
ABSTRACT This study introduces a realized volatility fuzzy time series (RV‐FTS) model that applies a fuzzy c‐means clustering algorithm to estimate time‐varying c$$ c $$ latent volatility states and their corresponding membership degrees. These memberships are used to construct a fuzzified volatility estimate as a weighted average of cluster centroids.
Shafqat Iqbal, Štefan Lyócsa
wiley   +1 more source

Eventology versus contemporary theories of uncertainty [PDF]

The development of probability theory together with the Bayesian approach in the three last centuries is caused by two factors: the variability of the physical phenomena and partial ignorance about them.
Vorobyev, Oleg
core   +1 more source

Imprecise Probabilities and Unstable Betting Behaviour [PDF]

Noûs, 2016
AbstractMany have argued that a rational agent's attitude towards a proposition may be better represented by a probability range than by a single number. I show that in such cases an agent will have unstable betting behaviour, and so will behave in an unpredictable way.
openaire   +2 more sources

Do Prices Matter for Healthcare Accessibility? Evidence From a Means‐Tested Complementary Health Insurance in France

Health Economics, EarlyView.
ABSTRACT In France, the Couverture Maladie Universelle Complémentaire (CMU‐C) scheme is a means‐tested, state‐financed, complementary health insurance program that fully covers healthcare. Using administrative claims data and a staggered difference‐in‐differences approach, we estimate the impact of enrollment in the program on healthcare utilization ...
Benoît Carré, Florence Jusot, Jérôme Wittwer   +2 more
wiley   +1 more source

Attitude toward imprecise information [PDF]

This paper presents an axiomatic model of decision making under uncertainty which incorporates objective but imprecise information. Information is assumed to take the form of a probability-possibility set, that is, a set $P$ of probability measures on ...
Jean-Christophe Vergnaud, Jean-Marc Tallon, Takashi Hayashi, Thibault Gajdos   +3 more
core  

Minimum Wages, the Earned Income Tax Credit, and Mental Health Around Pregnancy

Health Economics, EarlyView.
ABSTRACT This study estimates the effects on perinatal mental health of the state's minimum wage and earned income tax credit (EITC), controlling for other policies and state‐level factors. Using data from the Pregnancy Risk Assessment Monitoring System for 2012–2018 births we find robust evidence that minimum wages and EITC levels reduce depression ...
Bryce J. Stanley, Karen Smith Conway
wiley   +1 more source

Medicare Part D and Hospital Admissions due to Antimicrobial Resistance

Health Economics, EarlyView.
ABSTRACT Antimicrobial resistance (AMR) has been increasing rapidly in the United States despite government efforts to contain its spread. Both under‐utilization and overuse of prescribed antimicrobials contribute to rising resistance. The introduction of Medicare Part D in 2006 expanded prescription drug coverage for the elderly, including coverage ...
Ricardo B. Ang III
wiley   +1 more source

Assessing compensation and organizational variation with imperfect data: An application of count-based indices of variation

International Journal of Management and Data Analytics
An accurate assessment of human capital or labor force variation in organizations is predicated upon collecting error-free data. When organizations report imprecise human capital or labor force data, problematic data analytic issues arise because the ...
Salomon Alcocer Guajardo
doaj  

Precise Propagation of Upper and Lower Probability Bounds in System P

, 2000
In this paper we consider the inference rules of System P in the framework of coherent imprecise probabilistic assessments. Exploiting our algorithms, we propagate the lower and upper probability bounds associated with the conditional assertions of a ...
Gilio, Angelo
core  

Estimating Treatment Effects With Limited Exogeneity: A Machine Learning Approach to Selection Bias

International Studies of Economics, EarlyView.
ABSTRACT This paper presents a novel method for estimating treatment effects in cases where prior knowledge of the exogeneity of the treatment variable is limited. We employ a machine learning technique, double selection via Lasso, to identify a robust set of control variables without requiring prior assumptions about their specific identities or ...
Rui Sun, Shiyi Chen
wiley   +1 more source