Adriana Cornea‐Madeira
Biographic Data
| ID | 8777416 |
|---|---|
| NAME | Adriana Cornea‐Madeira |
| GIVEN NAMES | Adriana |
| FAMILY NAME | Cornea‐Madeira |
| SIGNATURE | MADEIRA A C |
| AFFILIATIONS | University of York |
| ORCID | 0000-0002-0889-7145 |
| VERIFIED | Yes |
| TOTAL WORKS | 4 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 4 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2014 |
| LATEST PUBLICATION YEAR | 2022 |
| H-INDEX | 0 |
Econometric Analysis of Switching Expectations in UK Inflation
We estimate with UK data a Phillips curve model with backward‐looking and forward‐looking methods of determining inflation expectations and with agents switching between these based on their recent performance. We find that, while on average backward‐looking and forward‐looking methods have about equal weight, there are considerable movements in the weight given to each method. We show this model has better in‐sample fit than other Phillips curve…
Behavioral Heterogeneity in U.S. Inflation Dynamics
In this article we develop and estimate a behavioral model of inflation dynamics with heterogeneous firms. In our stylized framework there are two groups of price setters, fundamentalists and random walk believers. Fundamentalists are forward-looking in the sense that they believe in a present-value relationship between inflation and real marginal costs, while random walk believers are backward-looking, using the simplest rule of thumb, naive exp…
The Explicit Formula for the Hodrick-Prescott Filter in a Finite Sample
We derive the exact expression for the weights of the Hodrick-Prescott (HP) filter in a finite sample without making any assumptions about the statistical properties of the time series. We use the results to give insights into the properties of the HP filter and to build a fast algorithm with computational improvements by a factor of up to three times in samples typical in economics
A Parametric Bootstrap for Heavy-Tailed Distributions
It is known that Efron’s bootstrap of the mean of a distribution in the domain of attraction of the stable laws with infinite variance is not consistent, in the sense that the limiting distribution of the bootstrap mean is not the same as the limiting distribution of the mean from the real sample. Moreover, the limiting bootstrap distribution is random and unknown. The conventional remedy for this problem, at least asymptotically, is either the m…
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A Parametric Bootstrap for Heavy-Tailed Distributions
It is known that Efron’s bootstrap of the mean of a distribution in the domain of attraction of the stable laws with infinite variance is not consistent, in the sense that the limiting distribution of the bootstrap mean is not the same as the limiting distribution of the mean from the real sample. Moreover, the limiting bootstrap distribution is random and unknown. The conventional remedy for this problem, at least asymptotically, is either the m…
The Explicit Formula for the Hodrick-Prescott Filter in a Finite Sample
We derive the exact expression for the weights of the Hodrick-Prescott (HP) filter in a finite sample without making any assumptions about the statistical properties of the time series. We use the results to give insights into the properties of the HP filter and to build a fast algorithm with computational improvements by a factor of up to three times in samples typical in economics
Behavioral Heterogeneity in U.S. Inflation Dynamics
In this article we develop and estimate a behavioral model of inflation dynamics with heterogeneous firms. In our stylized framework there are two groups of price setters, fundamentalists and random walk believers. Fundamentalists are forward-looking in the sense that they believe in a present-value relationship between inflation and real marginal costs, while random walk believers are backward-looking, using the simplest rule of thumb, naive exp…
Econometric Analysis of Switching Expectations in UK Inflation
We estimate with UK data a Phillips curve model with backward‐looking and forward‐looking methods of determining inflation expectations and with agents switching between these based on their recent performance. We find that, while on average backward‐looking and forward‐looking methods have about equal weight, there are considerable movements in the weight given to each method. We show this model has better in‐sample fit than other Phillips curve…
Complex Systems and Time Series Analysis (3 works) · Econometrics (3 works) · Economics (3 works) · Mathematics (3 works) · Monetary Policy and Economic Impact (3 works) · Statistics (3 works) · Applied Mathematics (2 works) · Computer Science (2 works) · Financial Risk and Volatility Modeling (2 works) · Macroeconomics (2 works)