Relevant bibliographies by topics / Seasonal Unit Root Test

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'Seasonal Unit Root Test'

Author: Grafiati
Published: 4 June 2021
Last updated: 13 February 2022

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Journal articles on the topic "Seasonal Unit Root Test"

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Caner, Mehmet. "A Locally Optimal Seasonal Unit-Root Test." Journal of Business & Economic Statistics 16, no. 3 (July 1998): 349. http://dx.doi.org/10.2307/1392511.

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Caner, Mehmet. "A Locally Optimal Seasonal Unit-Root Test." Journal of Business & Economic Statistics 16, no. 3 (July 1998): 349–56. http://dx.doi.org/10.1080/07350015.1998.10524774.

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Depalo, Domenico. "A Seasonal Unit-Root Test with Stata." Stata Journal: Promoting communications on statistics and Stata 9, no. 3 (September 2009): 422–38. http://dx.doi.org/10.1177/1536867x0900900305.

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Popp, Stephan. "Modified seasonal unit root test with seasonal level shifts at unknown time." Economics Letters 97, no. 2 (November 2007): 111–17. http://dx.doi.org/10.1016/j.econlet.2007.02.026.

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Kurozumi, Eiji. "THE LIMITING PROPERTIES OF THE CANOVA AND HANSEN TEST UNDER LOCAL ALTERNATIVES." Econometric Theory 18, no. 5 (July 17, 2002): 1197–220. http://dx.doi.org/10.1017/s0266466602185082.

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This paper investigates the limiting properties of the Canova and Hansen test, testing for the null hypothesis of no unit root against seasonal unit roots, under a sequence of local alternatives with the model extended to have seasonal dummies and trends or no deterministic term and also only seasonal dummies. We derive the limiting distribution of the test statistic and its characteristic function under local alternatives. We find that the local limiting power is an inverse function of the spectral density at frequency π (π/2) when we test against a negative unit root (annual unit roots). We also theoretically show that the local limiting power of the Canova and Hansen test against a negative unit root (annual unit roots) does not increase when the true process has annual unit roots (a negative unit root) but not a negative unit root (annual unit roots), which has been observed in Monte Carlo simulations in such research as Caner (1998, Journal of Business and Economic Statistics 16, 349–356), Canova and Hansen (1995, Journal of Business and Economic Statistics 13, 237–252), and Hylleberg (1995, Journal of Econometrics 69, 5–25).
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Castro, Tomas del Barrio, and Denise R. Osborn. "TESTING FOR SEASONAL UNIT ROOTS IN PERIODIC INTEGRATED AUTOREGRESSIVE PROCESSES." Econometric Theory 24, no. 4 (April 4, 2008): 1093–129. http://dx.doi.org/10.1017/s0266466608080420.

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This paper examines the implications of applying the Hylleberg, Engle, Granger, and Yoo (1990, Journal of Econometrics 44, 215–238) (HEGY) seasonal root tests to a process that is periodically integrated. As an important special case, the random walk process is also considered, where the zero-frequency unit root t-statistic is shown to converge to the Dickey–Fuller distribution and all seasonal unit root statistics diverge. For periodically integrated processes and a sufficiently high order of augmentation, the HEGY t-statistics for unit roots at the zero and semiannual frequencies both converge to the same Dickey–Fuller distribution. Further, the HEGY joint test statistic for a unit root at the annual frequency and all joint test statistics across frequencies converge to the square of this distribution. Results are also derived for a fixed order of augmentation. Finite-sample Monte Carlo results indicate that, in practice, the zero-frequency HEGY statistic (with augmentation) captures the single unit root of the periodic integrated process, but there may be a high probability of incorrectly concluding that the process is seasonally integrated.
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Cáceres-Hernández, José J., and Gloria Martín-Rodríguez. "Stationarity of seasonal patterns in weekly agricultural prices." Spanish Journal of Agricultural Research 16, no. 3 (October 23, 2018): e0109. http://dx.doi.org/10.5424/sjar/2018163-12937.

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Weekly series of agricultural prices usually exhibit seasonal variations and the stationarity of these variations should be taken into account to analyse price relationships. However, unit root tests at seasonal frequencies are unlikely to have good power properties. Furthermore, movements in actual price series are often not as expected when unit roots are present. Therefore, stationarity tests at seasonal frequencies also need to be applied. In this paper, a procedure to test for the null hypothesis of stationarity at seasonal frequencies was extended to the weekly case. Once critical values were obtained by simulation exercises, unit root and stationarity tests were applied to weekly retail prices of different agricultural commodities in Spain. The most relevant finding was that many unit roots that seasonal unit root tests failed to reject did not seem to be present from the results of seasonal stationarity tests, whereas seasonal unit root tests led to the rejection of some unit roots that seemed to be present according to the results of seasonal stationarity tests. In conclusion, unit root tests should be complemented with stationarity tests before making decisions about the behaviour of seasonal patterns.
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Narayan, Paresh Kumar, and Stephan Popp. "An application of a new seasonal unit root test to inflation." International Review of Economics & Finance 20, no. 4 (October 2011): 707–16. http://dx.doi.org/10.1016/j.iref.2011.01.001.

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Halim, Siana, and Indriati N. Bisono. "Automatic seasonal auto regressive moving average models and unit root test detection." International Journal of Management Science and Engineering Management 3, no. 4 (January 2008): 266–74. http://dx.doi.org/10.1080/17509653.2008.10671053.

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RODRIGUES, PAULO M. M. "NEAR SEASONAL INTEGRATION." Econometric Theory 17, no. 1 (February 2001): 70–86. http://dx.doi.org/10.1017/s0266466601171033.

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This paper presents asymptotic results for the seasonal unit root test proposed by Hylleberg, Engle, Granger and Yoo (1990, Journal of Econometrics 44, 215–238) in a near integration context. The findings are important in that they provide the asymptotic power functions of the Hylleberg et al. statistics when the characteristic roots of a seasonal process are local to unity. These conclusions extend the available asymptotic results for this test and serve as a framework for the potential development of more powerful test procedures.
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Dissertations / Theses on the topic "Seasonal Unit Root Test"

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Sayin, Ipek. "Modelling Electricity Demand In Turkey For 1998-2011." Master's thesis, METU, 2013. http://etd.lib.metu.edu.tr/upload/12615515/index.pdf.

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This thesis estimates the quarterly electricity demand of Turkey. First of all proper seasonal time series model are found for the variables: electricity demand, temperature, gross domestic product and electricity price. After the right seasonal time series model are found Hylleberg, Engle, Granger and Yoo (1990) test is applied to each variable. The results of the test show that seasonal unit roots exist for the electricity price even it cannot be seen at the graph. The other variables have no seasonal unit roots when the proper seasonal time series model is chosen. Later, the cointegration is tested by looking at the vector autoregressive model. As the cointegration is seen vector error correction model is found. There is long-run equilibrium when the price is the dependent variable and independent variable is gross domestic product. Temperature is taken as exogenous variable and demand is not statistically significant.
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Wei, Jianxin. "On Bootstrap Evaluation of Tests for Unit Root and Cointegration." Doctoral thesis, Uppsala universitet, Statistiska institutionen, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-233885.

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This thesis is comprised of five papers that all relate to bootstrap methodology in analysis of non-stationary time series. The first paper starts with the fact that the Dickey-Fuller unit root test using asymptotic critical value has bad small sample performance. The small sample correction proposed by Johansen (2004) and bootstrap are two effective methods to improve the performance of the test. In this paper we compare these two methods as well as analyse the effect of bias-adjusting through a simulation study. We consider AR(1) and AR(2) models and both size and power properties are investigated. The second paper studies the asymptotic refinement of the bootstrap cointegration rank test. We expand the test statistic of a simplified VECM model and a Monte Carlo simulation was carried out to verify that the bootstrap test gives asymptotic refinement. The third paper focuses on the number of bootstrap replicates in bootstrap Dickey-Fuller unit root test. Through a simulation study, we find that a small number of bootstrap replicates are sufficient for a precise size, but, with too small number of replicates, we will lose power when the null hypothesis is not true. The fourth and last paper of the thesis concerns unit root test in panel setting focusing on the test proposed by Palm, Smeekes and Urbain (2011). In the fourth paper, we study the robustness of the PSU test with comparison with two representative tests from the second generation panel unit root tests. In the last paper, we generalise the PSU test to the model with deterministic terms. Two different methods are proposed to deal with the deterministic terms, and the asymptotic validity of the bootstrap procedure is theoretically checked. The small sample properties are studied by simulations and the paper is concluded by an empirical example.

Ogiltigt ISBN: 978-91-554-9069-0

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Neumann, Cornelia. "Purchasing Power Parity in the European Union A panel unit root test /." St. Gallen, 2008. http://www.biblio.unisg.ch/org/biblio/edoc.nsf/wwwDisplayIdentifier/05604160001/$FILE/05604160001.pdf.

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Uysal, Ela. "Application Of Nonlinear Unit Root Tests And Threshold Autoregressive Models." Master's thesis, METU, 2012. http://etd.lib.metu.edu.tr/upload/12614878/index.pdf.

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Popularity of nonlinear threshold models and unit root tests has increased after the recent empirical studies concerning the effects of business cycles on macroeconomic data. These studies have shown that an economic variable may react differently in response to downturns and recoveries in a business cycle. Inspiring from empirical results, this thesis investigates dynamics of Turkish key macroeconomic data, namely capacity utilization rate, growth of import and export volume indices, growth of gross domestic product, interest rate for cash loans in Turkish Liras and growth of industrial production index. Estimation results imply that capacity utilization rate and growth of industrial production index show M-TAR type nonlinear stationary behavior according to the unit root test proposed by Enders and Granger (1998).
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Shin, Sukha. "Covariate unit root test under structural change and its application to the relation between income and consumption." Connect to resource, 2002. http://rave.ohiolink.edu/etdc/view.cgi?acc%5Fnum=osu1261245043.

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Hamadeh, Lina. "Periodically integrated models : estimation, simulation, inference and data analysis." Thesis, University of Manchester, 2016. https://www.research.manchester.ac.uk/portal/en/theses/periodically-integrated-models-estimation-simulation-inference-and-data-analysis(f7b345e9-bad7-424a-9746-bfe771d7ba8c).html.

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Periodically correlated time series generally exist in several fields including hydrology, climatology, economics and finance, and are commonly modelled using periodic autoregressive (PAR) model. For a time series with stochastic periodic trend, for which a unit root is expected, a periodically integrated autoregressive PIAR model with periodic and/or seasonal unit root has been shown to be a satisfactory model. The existing theory used the multivariate methodology to study PIAR models. However, this theory is convoluted, majority of it only developed for quarterly time series and its generalisation to time series with larger number of periods is quite cumbersome. This thesis studies the existing theory and highlights its restrictions and flaws. It provides a coherent presentation of the steps for analysing PAR and PIAR models for different number of periods. It presents the different unit roots representations and compares the performance of different unit root tests available in literature. The restrictions of existing studies gave us the impetus to develop a unified theory that gives a clear understanding of the integration and unit roots in the periodic models. This theory is based on the spectral information of the multi-companion matrix of the periodic models. It is more general than the existing theory, since it can be applied to any number of periods whereas the existing methods are developed for quarterly time series. Using the multi-companion method, we specify and estimate the periodic models without the need to extract complicated restrictions on the model parameters corresponding to the unit roots, as required by NLS method. The multi-companion estimation method performed well and its performance is equivalent to the NLS estimation method that has been used in the literature. Analysing integrated multivariate models is a problematic issue in time series. The multi-companion theory provides a more general approach than the error correction method that is commonly used to analyse such time series. A modified state state representation for the seasonal periodically integrated autoregressive (SPIAR) model with periodic and seasonal unit roots is presented. Also an alternative state space representations from which the state space representations of PAR, PIAR and the seasonal periodic autoregressive (SPAR) models can be directly obtained is proposed. The seasons of the parameters in these representations have been clearly specified, which guarantees correct estimated parameters. Kalman filter have been used to estimate the parameters of these models and better estimation results are obtained when the initial values were estimated rather than when they were given.
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Arvidsson, Mattias. "An empirical examination of the Fisher hypothesis in Sweden." Thesis, Örebro universitet, Handelshögskolan vid Örebro Universitet, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:oru:diva-25883.

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Guo, Yuanxiang. "Chinese wheat price analysis - with application of cointegration and Granger causality test." Thesis, Georgia Institute of Technology, 2013. http://hdl.handle.net/1853/52978.

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Traditional demonstration of price fluctuation in the wheat market, by the theory of supply and demand is not comprehensive enough. With limited understanding of macroeconomic effects on the wheat market, accurate prediction of wheat price is impossible. Given the Chinese self—sustainable food policy, grain imports is a sensitive topic which may incur fierce argument. In this paper, however, I emphasize effect of exchange rate on nominal wheat price. By application of the cointegration theory, CPI shows slight negative correlation with nominal wheat price, yet GDP and population move in the same direction as the wheat price. The cointegration study of exchange rate implies, with appreciating Chinese RMB, domestic buyers incline to purchase wheat from the cheaper foreign market. According to the Granger causality test, the whole package of variables suggests significant causal relation with the wheat price.
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Mendonça, Francisco António Teixeira. "Double unit tests in the presence of structural breaks." Master's thesis, Instituto Superior de Economia e Gestão, 2017. http://hdl.handle.net/10400.5/14894.

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Mestrado em Econometria Aplicada e Previsão
Apresentam-se dois testes estatísticos que permitem averiguar a existência de duas raízes unitárias numa série temporal univariada que contenha um quebra estrutural na função determinística. Os testes foram aplicados a várias séries económicas, e encontrou-se evidência estatística que suporta a hipótese nula.
We present two statistical tests that to verify the existence of two unit roots in a univariate time series that contains a structural break in the deterministic function. The tests were applied to several economic series, and statistical evidence supporting the null hypothesis was found.
info:eu-repo/semantics/publishedVersion
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Göhler, Andreas. "Einheitswurzeltests : (A)DF-versus Cauchyverfahren ; ein Gütevergleich unter Berücksichtigung verschiedener Trendbereinigungsverfahren /." Aachen : Shaker, 2006. http://www.gbv.de/dms/zbw/509082149.pdf.

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Books on the topic "Seasonal Unit Root Test"

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Kunst, Robert M. A Likelihood-Ratio Test for Seasonal Unit Roots. Wien: Inst.fur Hohere Studien, 1988.

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Taylor, A. M. Robert. On the asymptotic properties of some seasonal unit root tests. Birmingham: University of Birmingham, Department of Economics, 2002.

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J, Smith Richard. Likelihood ratio tests for seasonal unit roots. Bristol: University of Bristol, Department of Economics, 1998.

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Leybourne, S. J. A simple test for a unit root. Nottingham: University of Nottingham, Dept. of Economics, 1992.

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Mohanty, Prabir Kumar. Does seasonal pattern in Indian stock returns contain a unit root? Bangalore: Institute for Social and Economic Change, 2000.

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Hjalmarsson, Erik. A residual-based cointegration test for near unit root variables. Washington, D.C: Federal Reserve Board, 2007.

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McCleary, Richard, David McDowall, and Bradley J. Bartos. Noise Modeling. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780190661557.003.0003.

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Chapter 3 introduces the Box-Jenkins AutoRegressive Integrated Moving Average (ARIMA) noise modeling strategy. The strategy begins with a test of the Normality assumption using a Kolomogov-Smirnov (KS) statistic. Non-Normal time series are transformed with a Box-Cox procedure is applied. A tentative ARIMA noise model is then identified from a sample AutoCorrelation function (ACF). If the sample ACF identifies a nonstationary model, the time series is differenced. Integer orders p and q of the underlying autoregressive and moving average structures are then identified from the ACF and partial autocorrelation function (PACF). Parameters of the tentative ARIMA noise model are estimated with maximum likelihood methods. If the estimates lie within the stationary-invertible bounds and are statistically significant, the residuals of the tentative model are diagnosed to determine whether the model’s residuals are not different than white noise. If the tentative model’s residuals satisfy this assumption, the statistically adequate model is accepted. Otherwise, the identification-estimation-diagnosis ARIMA noise model-building strategy continues iteratively until it yields a statistically adequate model. The Box-Jenkins ARIMA noise modeling strategy is illustrated with detailed analyses of twelve time series. The example analyses include non-Normal time series, stationary white noise, autoregressive and moving average time series, nonstationary time series, and seasonal time series. The time series models built in Chapter 3 are re-introduced in later chapters. Chapter 3 concludes with a discussion and demonstration of auxiliary modeling procedures that are not part of the Box-Jenkins strategy. These auxiliary procedures include the use of information criteria to compare models, unit root tests of stationarity, and co-integration.
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McGraw-Hill. Algebra 2, Student Edition. Glencoe/McGraw-Hill, 2002.

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McGraw-Hill. Algebra 2, Student Edition. Glencoe/McGraw-Hill, 1998.

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McGraw-Hill. Algebra 2, Student Edition. Glencoe/McGraw-Hill, 2006.

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Book chapters on the topic "Seasonal Unit Root Test"

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Salish, Nazarii, and Paulo M. M. Rodrigues. "Panel Seasonal Unit Root Tests: An Application to Tourism." In Tourism Economics, 183–210. Heidelberg: Physica-Verlag HD, 2011. http://dx.doi.org/10.1007/978-3-7908-2725-5_12.

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Das, Panchanan. "Panel Unit Root Test." In Econometrics in Theory and Practice, 513–40. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-32-9019-8_17.

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Fellag, Hocine, and Lynda Atil. "Bayesian Approach of the Unit Root Test." In International Encyclopedia of Statistical Science, 97–99. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-04898-2_134.

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Davis, Richard A., Meiching Chen, and William T. M. Dunsmuir. "Inference for Seasonal Moving Average Models With a Unit Root." In Athens Conference on Applied Probability and Time Series Analysis, 160–76. New York, NY: Springer New York, 1996. http://dx.doi.org/10.1007/978-1-4612-2412-9_12.

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de Peretti, Christian, Carole Siani, and Mario Cerrato. "A Bootstrap Artificial Neural Network Based Heterogeneous Panel Unit Root Test in Case of Cross Sectional Independence." In Neural Information Processing, 441–50. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-10677-4_50.

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Yao, Xidan, and Dunhong Yao. "A Study on the Influence of Economic Growth on Urban-Rural Income Gap in Five Northwest Provinces Based on Unit Root and Co-integration Test." In Lecture Notes in Computer Science, 290–302. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-78609-0_25.

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Dickey, David. "Normally Distributed Seasonal Unit Root Tests." In Economic Time Series, 383–401. Chapman and Hall/CRC, 2012. http://dx.doi.org/10.1201/b11823-23.

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"Seasonal Unit Root Processes." In The Econometric Analysis of Seasonal Time Series, 42–92. Cambridge University Press, 2001. http://dx.doi.org/10.1017/cbo9781139164009.005.

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Sinha, Madhabendra, and Partha Pratim Sengupta. "FDI and Trade in Services Towards Sustainable Economic Growth." In Wealth Creation and Poverty Reduction, 369–81. IGI Global, 2020. http://dx.doi.org/10.4018/978-1-7998-1207-4.ch021.

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The paper empirically investigates the inter-linkage between FDI inflow and international trade in service sector in India. Service sector emerges as the fastest growing sector worldwide during current phase of globalization, contributing more than 60 percent of output and almost 35 percent of trade in global economy. The sector also accounted for 63 percent of global stock of FDI. With hosting a large amount of FDI inflow, Indian service sector is also identified globally due to its substantial improvement in growth and export in international market. So there needs a study to explore the theoretically established causal relationship between FDI inflow and international trade in services towards sustainable and service led economic growth in India. The authors collect monthly data from DIPP, Government of India and RBI over a globally witnessed emerging period from January 2009 to June 2016 and apply ADF and PP unit root tests followed by least square estimation after testing the seasonal effects. Their findings imply unidirectional causality between FDI inflow and export Indian services.
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Zhao, Chun-Yan, and Shi-Jing Nan. "A new notion to test unit root for the LSTAR model." In Computer, Intelligent Computing and Education Technology, 599–603. CRC Press, 2014. http://dx.doi.org/10.1201/b16698-130.

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Conference papers on the topic "Seasonal Unit Root Test"

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Şanlı, Sera, and Mehmet Özmen. "A Different Look at Cointegration Relationship between Quarterly Inflation Rates and Growth via Seasonal Integration Tests." In International Conference on Eurasian Economies. Eurasian Economists Association, 2019. http://dx.doi.org/10.36880/c11.02293.

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Detecting the direction of inflation-growth relationship has been a controversial issue in terms of the theoretical framework, notedly since the rise of Mundell-Tobin effect which is based upon the assumption of substitutability between money and capital. In this study, it has been aimed to investigate the cointegrating relationship and its direction between inflation and economic growth covering the period 1998Q1:2014Q4 for Turkey as grounded on the testing sequence that is illustrated by Ilmakunnas (1990) in order to handle unit root testing in a seasonal context by testing the appropriate order of differencing and concerns with the case where SI(2,1) (seasonally integrated of order (2,1)) is the maximum order of seasonal integration. It has been also utilized from ADF unit root test and DHF, HEGY & OCSB seasonal unit root tests in seasonal integration analysis. In the study, five cointegration regressions have been considered in the level, seasonally averaged, quarterly differenced, first differenced and twice differenced forms and two series have been found to have the same degree of seasonal integration as SI(1,1). Applying various residual tests have revealed the presence of a cointegrating relationship between two variables. In addition, the inflation-growth relationship in Turkey has been concluded to perform in an opposite direction.
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Halim, S., I. N. Bisono, Melissa, and C. Thia. "Automatic seasonal auto regressive moving average models and unit root test detection." In 2007 IEEE International Conference on Industrial Engineering and Engineering Management. IEEE, 2007. http://dx.doi.org/10.1109/ieem.2007.4419368.

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Özmen, Mehmet, and Sera Şanlı. "Seasonal Cointegration Approach on Expenditure Based Gross Domestic Product and Its Some Sub-Components for Turkey." In International Conference on Eurasian Economies. Eurasian Economists Association, 2017. http://dx.doi.org/10.36880/c09.01980.

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In this study, it has been aimed to investigate the existence of co-integration relationship between quarterly gross domestic product (GDP), final consumption expenditures of resident households (CONS), exports of goods and services (EXP), government final consumption expenditures (GOV) and private sector machinery-equipment (PRIEQ) series for the period 1998Q1-2014Q4 for Turkey. Since, Engle and Granger (1987) cointegration test does not take unit roots at seasonal frequencies into account; seasonal cointegration approach proposed by Engle, Granger, Hylleberg and Lee (EGHL) (1993) has been conducted in order to be able to detect the long-run equilibrium relationship among variables which are integrated at the same seasonal frequency. With the aim of determining the stationarity order of series, HEGY seasonal unit root test has been applied. Consequently, there has been found a cointegrating relationship only between GDP and GOV series at quarterly frequencies for only the auxiliary regression including constant term and seasonal dummies.
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Wong, Kau-Fui V., Diego Valde´s, Joshua Goad, and Jesse Losada. "An Alternative Field Test for Spot Air Conditioning Units." In ASME 2007 International Mechanical Engineering Congress and Exposition. ASMEDC, 2007. http://dx.doi.org/10.1115/imece2007-41190.

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U.S. governmental standards require that newly produced air conditioners have a SEER (seasonal energy efficiency ratio) rating of over 13, Federal Register (2001), [1]. This rating is closely tied to the COP (coefficient of performance). In fact, the SEER is 3.792 times the COP. Since COP varies with temperature loads, a standard testing method requires the unit to be tested at standard conditions of temperature and humidity. This requires the use of expensive climate control chambers, where the system can be loaded to the specified temperatures. The scope of this paper proposes a simpler, less expensive method to test spot AC (air conditioning) units, as an alternative field test to ASHRAE (American Society of Heating, Refrigeration, and Air-Conditioning Engineers) Standard 128 (2001), [2]. By taking temperature measurements of the appropriate control volume, the COP can be calculated. To obtain steady state, the control volume will be treated as very large (or infinite), placing the unit to be tested outdoors or in a room big enough so that delta T will remain constant. Themocouples in conjunction with data logging software are used to take the temperature measurements, and the mass flow rate is measured by assuming uniform flow and placing a flow meter in the center of the air exhaust, on the evaporator side. The entire system can be assembled into a portable unit composed of a computer, thermocouples, flow meter and a digital multimeter, alternatively, a handheld relative humidity and temperature sensor can be used, ASHRAE (2003), [3]. This would allow not only testing of units before they go into production, but having technicians in the field test the efficiency of units already in operation. The need may be there since there could be a significant drop in the SEER between factory conditions and installed unit, due to variations in duct sizes, losses due to non-ideal installations. Owing to the fact that the COP varies with loading, and our testing method requires no artificial control over loading temperatures, the current study is being conducted to find if the AC unit can perform up to its rating. The second law COP at environmental loading conditions is also evaluated for each of the five AC units tested. The calculated COPII (based on exergy) of the AC units tested do not vary as much (percentage-wise) as the rated COP. Their relative detrimental effects to the environment are probably not that much different from each other.
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Bensalma, Ahmed. "A consistent test for unit root against fractional alternative." In 2013 5th International Conference on Modeling, Simulation and Applied Optimization (ICMSAO 2013). IEEE, 2013. http://dx.doi.org/10.1109/icmsao.2013.6552578.

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Hepsag, Aycan, and Barış Erkan Yazici. "DO DEVELOPING COUNTRIES FACE THE “MIDDLE INCOME TRAP”? EVIDENCE FROM A NOVEL UNIT ROOT TEST." In 3rd International Scientific Conference on Economics and Management. Association of Economists and Managers of the Balkans, Belgrade; Faculty of Management Koper; Doba Business School - Maribor; Integrated Business Faculty - Skopje; Faculty of Management - Zajecar, 2019. http://dx.doi.org/10.31410/eman.s.p.2019.117.

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Murphy, R. W., and V. D. Baxter. "Accelerated Life Test and Field Test Performance Results for an Integral Heat Pump Water Heater." In ASME 2004 International Mechanical Engineering Congress and Exposition. ASMEDC, 2004. http://dx.doi.org/10.1115/imece2004-60591.

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A residential heat pump water heater (HPWH) of integral-type design (heat pump unit mounted directly to tank with no water circulation pump) has undergone both durability and field performance testing. Results of two rounds of durability testing and evaluation of as-installed field efficiency vs ambient conditions at HPWH location are summarized in this paper. Ten of the HPWHs were run through an initial durability test designed to represent seven to ten years of normal compressor cycling to meet hot water needs of a residence. The first generation control system proved to be the least reliable component of the units with a 40% failure rate for its temperature input sensors and one complete system failure. After modification of the controls a second durability test was run with five units. There were essentially no operational failures during the second test. In parallel with the durability tests, HPWH units were installed in occupied residences at 18 US locations and field performance data were collected for 1–2 years. Results for two units with differing degrees of exposure to seasonal ambient air temperature and supply water temperature variations are presented and interpreted in this paper. For the first unit, installed in a conditioned space with well water supply, such seasonal temperature variations were small. The average field-measured coefficient of performance (COP) over a 75-week test period for this unit was 2.44 ±5% and weekly averages ranged from 9% below to 10% above the overall average. For the second unit, installed in an unconditioned space with city water supply, the seasonal temperature variations were substantial. Its average COP was 1.81 ±5% over a 104-week test period and weekly averages ranged from 38% below to 28% above that value.
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de Peretti, Christian, Carole Siani, and Mario Cerrato. "An artificial neural network based heterogeneous panel unit root test in case of cross sectional independence." In 2009 International Joint Conference on Neural Networks (IJCNN 2009 - Atlanta). IEEE, 2009. http://dx.doi.org/10.1109/ijcnn.2009.5178885.

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Milton, J. W. "A Review of Seasonal Dispatch Modeling Methods." In ASME 2005 Power Conference. ASMEDC, 2005. http://dx.doi.org/10.1115/pwr2005-50087.

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Rankine cycle power plants efficiency varies across the seasons due to changes in ambient air and cooling water temperatures. The size of this variation is influenced by the unit design. Test data collected on units to develop economic dispatch (input output) models produces an “as found” result. This result includes current imposed season influence and mechanical condition of the unit. With additional steps, these models can be adjusted to account for and quantify the seasonal efficiency changes. This paper will review the various methods used to account for these changes and evaluate the pros and cons of each method.
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Moradi, Mehdi, Julian Guerrero, Robert Rohling, and Septimiu E. Salcudean. "Preliminary results of an ultrasound segmentation method based on statistical unit-root test of B-scan radial intensity profiles." In 2009 IEEE International Ultrasonics Symposium. IEEE, 2009. http://dx.doi.org/10.1109/ultsym.2009.5442062.

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