Microdata Evidence on the Empirical Importance of Selection Effects in Menu-Cost Models

2017 ◽  
Vol 49 (8) ◽  
pp. 1803-1830 ◽  
Author(s):  
MIKAEL CARLSSON
Keyword(s):  
Selection Effects ◽  
Cost Models ◽  
Menu Cost

scholarly journals How Frequent Are Small Price Changes?

2014 ◽  
Vol 6 (2) ◽  
pp. 137-155 ◽  
Author(s):  
Martin Eichenbaum ◽  
Nir Jaimovich ◽  
Sergio Rebelo ◽  
Josephine Smith
Keyword(s):  
Price Index ◽  
Consumer Price Index ◽  
Empirical Work ◽  
Cost Models ◽  
Scanner Data ◽  
Micro Data ◽  
Price Changes ◽  
Nominal Rigidity ◽  
Menu Cost ◽  
Litmus Test

Recent empirical work suggests that small price changes are relatively common. This evidence has been used to criticize classic menu-cost models. In this paper, we use scanner data from a national supermarket chain and micro data from the Consumer Price Index to reassess the importance of small price changes. We argue that the vast majority of these changes are due to measurement error. We conclude that the evidence on the prevalence of small price changes is much too weak to be used as a litmus test of nominal rigidity models. (JEL C82, E31, L11, L81)

scholarly journals Inventories, Markups, and Real Rigidities in Menu Cost Models

2012 ◽  
Vol 80 (1) ◽  
pp. 249-276 ◽  
Author(s):  
Oleksiy Kryvtsov ◽  
Virgiliu Midrigan
Keyword(s):  
Cost Models ◽  
Menu Cost

scholarly journals Inventories, Markups, and Real Rigidities in Menu Cost Models

2009 ◽  
Author(s):  
Oleksiy Kryvtsov ◽  
Virgiliu Midrigan
Keyword(s):  
Cost Models ◽  
Menu Cost

From Hyperinflation to Stable Prices: Argentina’s Evidence on Menu Cost Models*

2018 ◽  
Vol 134 (1) ◽  
pp. 451-505 ◽  
Author(s):  
Fernando Alvarez ◽  
Martin Beraja ◽  
Martín Gonzalez-Rozada ◽  
Pablo Andrés Neumeyer
Keyword(s):  
Cost Models ◽  
Menu Cost

scholarly journals Five Facts about Prices: A Reevaluation of Menu Cost Models*

2008 ◽  
Vol 123 (4) ◽  
pp. 1415-1464 ◽  
Author(s):  
Emi Nakamura ◽  
Jón Steinsson
Keyword(s):  
Cost Models ◽  
Menu Cost

scholarly journals Large Shocks in Menu Cost Models

2012 ◽  
Author(s):  
Peter Karadi ◽  
Adam Reiff
Keyword(s):  
Cost Models ◽  
Menu Cost

ESTIMATED THRESHOLDS IN THE RESPONSE OF OUTPUT TO MONETARY POLICY: ARE LARGE POLICY CHANGES LESS EFFECTIVE?

2013 ◽  
Vol 18 (1) ◽  
pp. 41-64 ◽  
Author(s):  
Luiggi Donayre
Keyword(s):  
Monetary Policy ◽  
Empirical Literature ◽  
Monetary Shocks ◽  
Cost Models ◽  
Monetary Policy Shocks ◽  
Policy Variable ◽  
Menu Cost ◽  
Policy Shocks ◽  
Unobserved Components Model ◽  
Effect Of Monetary Policy

This paper investigates the potential sources of the mixed evidence found in the empirical literature studying asymmetries in the response of output to monetary policy shocks of different magnitudes. Further, it argues that such mixed evidence is a consequence of the exogenous imposition of the threshold that classifies monetary shocks as small or large. To address this issue, I propose an unobserved-components model of output, augmented by a monetary policy variable, which allows the threshold to be endogenously estimated. The results show strong statistical evidence that the effect of monetary policy on output varies disproportionately with the size of the monetary shock once the threshold is estimated. Meanwhile, the estimates of the model are consistent with a key implication of menu-cost models: smaller monetary shocks trigger a larger response on output.

The Development of Not-For-Profit Hospital Cost Models

1988 ◽  
Vol 6 (1) ◽  
pp. 35-48
Author(s):  
Greg M. Thibadoux ◽  
Nicholas Apostolou ◽  
Ira S. Greenberg
Keyword(s):  
Hospital Cost ◽  
Cost Models ◽  
For Profit ◽  
Not For Profit

On the Mathematical Basis of Zelen’s Prerandomized Designs

1985 ◽  
Vol 24 (03) ◽  
pp. 120-130 ◽  
Author(s):  
E. Brunner ◽  
N. Neumann
Keyword(s):  
Clinical Trial ◽  
Normal Distribution ◽  
Random Variables ◽  
Small Samples ◽  
Selection Effects ◽  
Sample Sizes ◽  
Mathematical Basis ◽  
Additional Assumptions

SummaryThe mathematical basis of Zelen’s suggestion [4] of pre randomizing patients in a clinical trial and then asking them for their consent is investigated. The first problem is to estimate the therapy and selection effects. In the simple prerandomized design (PRD) this is possible without any problems. Similar observations have been made by Anbar [1] and McHugh [3]. However, for the double PRD additional assumptions are needed in order to render therapy and selection effects estimable. The second problem is to determine the distribution of the statistics. It has to be taken into consideration that the sample sizes are random variables in the PRDs. This is why the distribution of the statistics can only be determined asymptotically, even under the assumption of normal distribution. The behaviour of the statistics for small samples is investigated by means of simulations, where the statistics considered in the present paper are compared with the statistics suggested by Ihm [2]. It turns out that the statistics suggested in [2] may lead to anticonservative decisions, whereas the “canonical statistics” suggested by Zelen [4] and considered in the present paper keep the level quite well or may lead to slightly conservative decisions, if there are considerable selection effects.

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