Production Smoothing Evidence from Physical-Product Data

Krane, Spencer; Braun, Susanne

doi:10.1086/261767

Cited by 97 publications

(53 citation statements)

References 13 publications

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“…Such invariance need not, however, obtain in finite samples, and, indeed, choice of left-hand-side variable seems to be important in practice: using various data sets, Ramey (1991), Kashyap and Wilcox (1993), and Krane and Braun (1991) found that estimated parameters sometimes varied widely for different choices. In the simulation analysis of section 5, we therefore experiment with alternative choices.…”

Section: The Estimatorsmentioning

confidence: 99%

Estimation and inference in the linear-quadratic inventory model

West

Wilcox

1994

Journal of Economic Dynamics and Control

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We summarize some recent work of ours on estimation and hypothesis testing on the parameters of the linear-quadratic inventory model. For some data-generating processes calibrated to estimates from some existing studies, this work uses (1) asymptotic theory to compare alternative estimators on the basis of the asymptotic efficiency of parameter estimates, (2) asymptotic theory and simulations to consider how likely one will be to get sharp estimates of the parameters of the model, and (3) simulations to see how accurately sized are hypothesis tests about the parameters of the model.

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Section: The Estimatorsmentioning

confidence: 99%

Estimation and inference in the linear-quadratic inventory model

West

Wilcox

1994

Journal of Economic Dynamics and Control

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“…Seasonal variations are noteworthy when analyzing inventory fluctuations [2] [3] [8]. Data from Japan 2 , the UK, Italy, and Germany are not seasonally adjusted.…”

Section: Datamentioning

confidence: 99%

“…Following a procedure described in an earlier report [3], BCa bootstrap confidence intervals of the variance ratio, i.e., the ratio of the variance of production to the variance of sales, are constructed by bootstrapping the deterministic parts of Equations (1), (2), and (3). That study [3] relied upon the assumption that the production and sales time series are expressible as the sum of the deterministic terms comprising seasonal dummy variables and the linear time trend, and the stationary random residuals.…”

Section: Bootstrappingmentioning

confidence: 99%

“…The hypothesis holds that the stock of inventories serves as a buffer in response to demand shifts that have not been forecast. The analytical framework used for the present study is an extension of models reported in the relevant literature [2] [3], which include the tenets that industrial data from the United States (US) and Taiwan can be converted to a stationary series in the way that the industrial production and sales series are regressed on the seasonal dummy variables and the linear time trend. Those models estimate the production and sales variances as the sum of the variances of the seasonal dummy variables and the variance of the residuals.…”

Section: Introductionmentioning

confidence: 99%

“…Wang's method is adopted here. However, the stationarity of the residuals was not tested formally in studies reported in the literature [2] [3]. In applying their methodological framework to macroeconomic data (such as gross domestic product (GDP), inventory investment, and aggregate sales), it is crucially important to test whether these variables are trendstationary.…”

Section: Introductionmentioning

confidence: 99%

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Production Smoothing in Developed Countries

Ginama¹,

Odaki²

2017

JMF

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This paper extends the method of regressing production and sales variables on a set of seasonal dummy variables and a linear trend for empirical tests on the production smoothing hypothesis of inventory investment. Unit root testing procedures form the basis for constructing the bootstrap confidence intervals for the ratio of the variance of production to the variance of sales. Models used to test for a unit root when there are structural breaks in the linear time trend are converted to equations comprising deterministic and stochastic components. A limiting distribution of the test statistic is derived. Bootstrap resampling is conducted over deterministic parts of the converted equations to construct confidence intervals for the relative variance ratio for G7 countries. Primary findings for these countries are production-counter smoothing phenomena.

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Temporal Aggregation and the Production Smoothing Model: Evidence from Electronic Parts and Components Manufacturing in Taiwan

Shen

2008

Lecture Notes in Electrical Engineering

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Production Smoothing Evidence from Physical-Product Data

Cited by 97 publications

References 13 publications

Estimation and inference in the linear-quadratic inventory model

Estimation and inference in the linear-quadratic inventory model

Production Smoothing in Developed Countries

Temporal Aggregation and the Production Smoothing Model: Evidence from Electronic Parts and Components Manufacturing in Taiwan

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