Reference health

Mixing Mixed Frequency and Diffusion Indices in Good Times and in Bad

2 of 47 checkable references need attention · checked 2026-08-26

At the dated check, the references listed below either did not resolve in Crossref or DataCite, or carried a retraction notice. Each one is shown with the registry record that put it there.

3 without a DOI — not checked. A reference deposited without a DOI is never matched by title or guessed at; it stays outside the checked set, and this line discloses that.

References needing attention

does not resolve to a known work10.2307/1392185

does not resolve to a known work10.2307/3584985

The 45 checked references that resolve

resolves10.1080/07474938.2010.481549

Seeing Inside the Black Box: Using Diffusion Index Methodology to Construct Factor Proxies in Large Scale Macroeconomic Time Series Environments

resolves10.1198/jbes.2009.07205

Real-Time Measurement of Business Conditions

resolves10.1257/aer.100.2.20

Real-Time Macroeconomic Monitoring: Real Activity, Inflation, and Interactions

resolves10.1111/1468-0262.00392

Inferential Theory for Factor Models of Large Dimensions

resolves10.1111/1468-0262.00273

Determining the Number of Factors in Approximate Factor Models

resolves10.1111/j.1468-0262.2006.00696.x

Confidence Intervals for Diffusion Index Forecasts and Inference for Factor-Augmented Regressions

resolves10.1198/073500106000000413

Determining the Number of Primitive Shocks in Factor Models

resolves10.1016/j.jeconom.2013.03.007

Principal components estimation and identification of static factors

resolves10.1002/for.2450

Incorporating the Beige Book into a Quantitative Index of Economic Activity

resolves10.3386/w11285

Understanding and Comparing Factor-Based Forecasts

resolves10.1016/j.jeconom.2005.01.027

Are more data always better for factor analysis?

resolves10.2139/ssrn.2002667

Markov-Switching Dynamic Factor Models in Real Time

resolves10.1016/j.ijforecast.2013.01.006

Green shoots and double dips in the euro area: A real time measure

resolves10.1080/07350015.2016.1186029

In-Sample Inference and Forecasting in Misspecified Factor Models

resolves10.24149/gwp268

Big Data Analytics: A New Perspective

resolves10.1016/s0304-4076(01)00071-9

Tests of equal forecast accuracy and encompassing for nested models

resolves10.1080/07474930500405683

Evaluating Direct Multistep Forecasts

resolves10.1198/073500108000000015

Macroeconomic Forecasting With Mixed-Frequency Data

resolves10.1016/j.jeconom.2014.04.011

Testing for structural stability of factor augmented forecasting models

resolves10.1111/j.1468-0084.2011.00642.x

Comparing Alternative Predictors Based on Large‐Panel Factor Models

resolves10.1080/01621459.1999.10474139

Prediction Intervals, Factor Analysis Models, and High-Dimensional Empirical Linear Prediction

resolves10.1093/acprof:oso/9780199641178.001.0001

Time Series Analysis by State Space Methods

resolves10.1162/003465300559037

The Generalized Dynamic-Factor Model: Identification and Estimation

resolves10.1198/016214504000002050

The Generalized Dynamic Factor Model

resolves10.1111/1467-937x.00053

Let's Get Real: A Factor Analytical Approach to Disaggregated Business Cycle Dynamics

resolves10.1016/j.jeconom.2005.01.004

Predicting volatility: getting the most out of return data sampled at different frequencies

resolves10.1080/07474930600972467

MIDAS Regressions: Further Results and New Directions

resolves10.1016/j.jeconom.2016.04.007

The econometric analysis of mixed frequency data sampling

resolves10.1198/016214506000001275

Determining the Number of Factors in the General Dynamic Factor Model

resolves10.7551/mitpress/6444.003.0013

State-Space Models with Markov Switching and Gibbs-Sampling

resolves10.1016/j.jeconom.2013.08.033

Forecasting financial and macroeconomic variables using data reduction methods: New empirical evidence

resolves10.2139/ssrn.2747473

Mining Big Data Using Parsimonious Factor, Machine Learning, Variable Selection and Shrinkage Methods

resolves10.2139/ssrn.2998263

Methods for Pastcasting, Nowcasting and Forecasting Using Factor-MIDAS: With an Application to Korean GDP

resolves10.1080/07350015.2015.1006773

Short-Term GDP Forecasting With a Mixed-Frequency Dynamic Factor Model With Stochastic Volatility

resolves10.1002/jae.695

A new coincident index of business cycles based on monthly and quarterly series

resolves10.1016/s0304-4076(00)00022-1

Robust out-of-sample inference

resolves10.3982/ecta6964

Testing Hypotheses About the Number of Factors in Large Factor Models

resolves10.1016/j.ijforecast.2009.08.004

Have economic models’ forecasting performance for US output growth and inflation changed over time, and when?

resolves10.2307/1412107

"General Intelligence," Objectively Determined and Measured

resolves10.1017/cbo9781139173735.005

A probability model of the coincident economic indicators

resolves10.1016/s0304-3932(99)00027-6

Forecasting inflation

resolves10.1198/073500102317351921

Macroeconomic Forecasting Using Diffusion Indexes

resolves10.1198/016214502388618960

Forecasting Using Principal Components From a Large Number of Predictors

resolves10.1093/acprof:oso/9780199237197.003.0007

Forecasting in Dynamic Factor Models Subject to Structural Instability*

resolves10.1016/s1574-0706(05)01004-9

Chapter 4 Forecast Combinations

The 3 references without a DOI — listed, not checked

no DOI — not checkedIs the Great Moderation Over? An Empirical Analysis

no DOI — not checkedMacroeconomic Forecasting Using Many Predictors

no DOI — not checkedref50

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