Admissible Clustering of Aggregator Components: A Necessary and Sufficient Stochastic Seminonparametric Test for Weak Separability

Barnett, William A.; Peretti, Philippe de

doi:10.1017/s1365100509090300

Cited by 9 publications

(22 citation statements)

References 34 publications

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“…Stage 1 has been conducted mostly using the nonparametric techniques of revealed preference analysis, introduced by Varian (). See, for example, Swofford and Whitney (, , ), Fleissig and Whitney (, ), de Peretti (2005), Jones and de Peretti (), Barnett and de Peretti (), and Mattson and de Peretti (); Elger et al. () also employ nonparametric weak separability tests to determine the optimal level of monetary aggregation in the United Kingdom.…”

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confidence: 99%

The Demand for Assets and Optimal Monetary Aggregation

Jadidzadeh¹,

Serletis²

2018

J of Money Credit Banking

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This paper uses a highly disaggregated demand system to estimate the degree of substitutability among monetary assets and to address the issue of optimal monetary aggregation in the United States. We address the problems of dimensionality and nonlinearity, estimating a very detailed monetary asset demand system encompassing the full range of assets based on the locally flexible normalized quadratic expenditure function. We treat the concavity property as a maintained hypothesis and provide evidence consistent with neoclassical microeconomic theory. Statistical tests reject the appropriateness of the aggregation assumptions for all the money measures published by the Federal Reserve as well as for a large number of groupings suggested by earlier studies. This supports and reinforces Barnett's (2016) assertion that we should employ the broadest M4 monetary aggregate published by the Center for Financial Stability.JEL codes: C3, C13, C51

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confidence: 99%

The Demand for Assets and Optimal Monetary Aggregation

Jadidzadeh¹,

Serletis²

2018

J of Money Credit Banking

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“…7 The dual user cost 6 To be an admissible quantity aggregator function, the function u must be weakly separable within the consumer's complete utility function over all goods and services. Producing a reliable test for weak separability is the subject of much intensive research, most recently by Barnett and Peretti (2008). 7 In equation 4, it is understood that the result is in continuous time, so the time subscripts are a short hand for functions of time.…”

Section: The Divisia Indexmentioning

confidence: 99%

Measurement Error in Monetary Aggregates: A Markov Switching Factor Approach

2009

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This paper compares the different dynamics of the simple sum monetary aggregates and the Divisia monetary aggregate indexes over time, over the business cycle, and across high and low inflation and interest rate phases. Although traditional comparisons of the series sometimes suggest that simple sum and Divisia monetary aggregates share similar dynamics, there are important differences during certain periods, such as around turning points. These differences cannot be evaluated by their average behavior. We use a factor model with regime switching. The model separates out the common movements underlying the monetary aggregate indexes, summarized in the dynamic factor, from individual variations in each individual series, captured by the idiosyncratic terms. The idiosyncratic terms and the measurement errors reveal where the monetary indexes differ. We find several new results. In general, the idiosyncratic terms for both the simple sum aggregates and the Divisia indexes display a business cycle pattern, especially since 1980. They generally rise around the end of high interest rate phasesa couple of quarters before the beginning of recessions -and fall during recessions to subsequently converge to their average in the beginning of expansions. We find that the major differences between the simple sum aggregates and Divisia indexes occur around the beginnings and ends of economic recessions, and during some high interest rate phases. We note the inferences' policy relevance, which is particularly dramatic at the broadest (M3) level of aggregation. Indeed, as Belongia (1996) has observed in this regard, "measurement matters."

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“…Thus, results based on this approach are often inconclusive. The test is extended in several directions by Swofford and Whitney (1994), Whitney (2003, 2005), Elger and Jones (2008), Cherchye et al (2015), and Barnett and de Peretti (2009), based upon de Peretti (2007). Varian (1985Varian ( , 1990 and Hjertstrand and Swofford (2014) can be referenced for extensions of GARP in stochastic environments.…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…For these reasons, to test for weak separability, in this paper, we will use the Barnett and de Peretti (2009) necessary and sufficient semi-nonparametric procedure and, in particular, a slightly extended version. The Barnett and de Peretti (2009) test is a two-step procedure. First, the necessary existence conditions for both an overall utility function and a (monetary) subutility function are tested under the assumption that quantity data are contaminated with noise (Step 1).…”

Section: Introductionmentioning

confidence: 99%

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Testing for Weak Separability Using Stochastic Semi-Nonparametric Tests: An Empirical Study on Us Data

Mattson¹,

Peretti²

2017

Macroecon. Dynam.

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In this paper, we use the weak separability criterion to check for the existence of six different monetary aggregates reported by the Center of Financial Stability (CFS). We implement an extended version of the semi-nonparametric tests introduced by Barnett and de Peretti on US monthly data from January 1967 to December 2012. The test, first, checks for the necessary existence conditions of an overall utility function and a monetary subutility function, and then tests for the separability of the latter. On different subsamples, our results suggest that only the DM1 aggregate meets the separability criterion. Implemented on macroeconomic data, we have tested a joint assumption about separability and the existence of a representative agent. Thus, the rejection of the null could also be due to the rejection of stringent Gorman's conditions. More advanced tests for weak separability are clearly required to confirm the results found in this paper.

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Admissible Clustering of Aggregator Components: A Necessary and Sufficient Stochastic Seminonparametric Test for Weak Separability

Cited by 9 publications

References 34 publications

The Demand for Assets and Optimal Monetary Aggregation

The Demand for Assets and Optimal Monetary Aggregation

Measurement Error in Monetary Aggregates: A Markov Switching Factor Approach

Testing for Weak Separability Using Stochastic Semi-Nonparametric Tests: An Empirical Study on Us Data

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