Skip to main content
Fachgebiete
Automobil + Motoren Bauwesen + Immobilien Business IT + Informatik Elektrotechnik + Elektronik Energie + Nachhaltigkeit Finance + Banking Management + Führung Marketing + Vertrieb Maschinenbau + Werkstoffe Versicherung + Risiko
DE
EN
Themenseiten
Organisationspsychologie Projektmanagement Marketing Smart Manufacturing
Bücher
Zeitschriften
Weitere Formate
Podcasts Webinare Technik Webinare Wirtschaft Kongresse Veranstaltungskalender Awards
Jetzt Einzelzugang starten
Zugang für Unternehmen
Referenzkunden
MTZ-Fachkongress

Antriebe und Energiesysteme von morgen


Austausch von Automobil- und Energiewirtschaft

Am 14./15. Mai geht es in Chemnitz um die Mobilitätswende durch Elektro- und Wasserstofffahrzeuge.
Erweiterte Suche
Anmelden
nach oben
Erschienen in:
Buchtitelbild

2023 | OriginalPaper | Buchkapitel

1. Einführung und Überblick

verfasst von : Vaibhavi Aher

Erschienen in: Statistische und mathematische Methoden in der Wirtschaft

Verlag: Springer Fachmedien Wiesbaden

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Einleitung des Herausgebers

Wie der Titel schon sagt, enthält dieser Abschnitt einige einführende Arbeiten zur Ökonometrie, die Ihnen helfen werden, das Thema zu verstehen und eine breitere Perspektive zu gewinnen.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Jetzt informieren
Nächstes Kapitel Analyse
Literatur
1.
R Development Core Team (2018) R: a language and environment for statistical computing
2.
Gil-Alana LA (2001) Testing stochastic cycles in macroeconomic time series. J Time Ser Anal 22(4):411–430CrossRef
3.
Gil-Alana LA, Gupta R (2014) Persistence and cycles in historical oil price data. Energy Econ 45:511–516CrossRef
4.
Caporale GM, Gil-Alana LA (2014) Long-run and cyclical dynamics in the US stock market. J Forecast 33(2):147–161CrossRef
5.
Caporale GM, Gil-Alana LA (2005) Fractional cointegration and aggregate money demand functions. Manch Sch 73(6):737–753CrossRef
6.
Gil-Alana LA (2005a) Fractional cyclical structures and business cycles in the specification of the US real output. Euro Res Stud J 8(1–2):99–126
7.
Granger CWJ (1980) Long memory relationships and the aggregation of dynamic models. J Econ 14(2):227–238CrossRef
8.
Bierens HJ (1997) Testing the unit root with drift hypothesis against nonlinear trend stationarity with an application to the US price level and interest rate. J Econ 81(1):29–64CrossRef
9.
Ben Nasr A, Ajmi AN, Gupta R (2014) Modeling the volatility of the Dow Jones Islamic market world index using a fractionally integrated time varying GARCH (FITVGARCH) model. App FIn Econ 24(14):993–1004CrossRef
10.
Bai J, Perron P (2003) Computation and analysis of multiple structural change models. J Appl Econ 18(1):1–22CrossRef
11.
Breusch TS, Pagan A (1980) The Lagrange multiplier test and its applications to model specification in econometrics. Rev Econ Stud 47:239–253CrossRef
12.
Bhargava A, Franzini L, Narendranathan W (1982) Serial correlation and the fixed effects model. Rev Econ Stud 49(4):533–549CrossRef
13.
Baltagi BH, Li Q (1995) Testing AR(1) against MA(1) disturbances in an error component model. J Econom 68:133–151CrossRef
14.
Bera AK, Sosa-Escudero W, Yoon M (2001) Tests for the error component model in the presence of local misspecification. J Econom 101:1–23CrossRef
15.
Hong Y, Kao C (2004) Wavelet-based testing for serial correlation of unknown form in panel models. Econometrica 72:1519–1563CrossRef
16.
Lee J, Hong Y (2001) Testing for serial correlation of unknown form using wavelet methods. Econom Theory 17:386–423CrossRef
17.
Choi I (2001) Unit root tests for panel data. J Int Money Finance 20:249–272CrossRef
18.
Hartung J (1999) A note on combining dependent tests of significance. Biom J 41(7):849–855CrossRef
19.
Hamilton JD (2018) Why you should never use the Hodrick-Prescott filter. Rev Econ Stat 100(5):831–843CrossRef
20.
Harvey AC, Jaeger A (1993) Detrending, stylized facts and the business cycle. J Appl Econom 8(3):231–247CrossRef
21.
Cogley T, Nason JM (1995) Effects of the Hodrick–Prescott filter on trend and difference stationary time series implications for business cycle research. J Econ Dyn Control 19(1):253–278CrossRef
22.
Pollock D (2013a) Cycles, syllogisms and semantics: examining the idea of spurious cycles. J Time Ser Econom 6(1):81–102
23.
Christiano LJ, Fitzgerald TJ (2003) The band pass filter. Int Econ Rev 44(2):435–465CrossRef
24.
Baxter M, King RG (1999) Measuring business cycles: approximate band-pass filters for economic time series. Rev Econ Stat 81(4):575–593CrossRef
25.
Roehner BM, Sornette D (2000) “Thermometers” of speculative frenzy. Eur Phys J B Condens Matter Complex Syst 16:729–739CrossRef
26.
Greenwood R, Shleifer A (2014) Expectations of returns and expected returns. Rev Financ Stud 27(3):714–746CrossRef
27.
Carro A, Toral R, San Miguel M (2015) Markets, herding and response to external information. PLoS ONE 10(7):e0133287CrossRef
28.
Simon H (1972) Theories of bounded rationality. In: McGuire CB, Radner R (eds) Decision and organization. North-Holland, Amsterdam, pp 161–176
29.
Kahneman D (2003) Maps of bounded rationality: psychology for behavioral economics. Am Econ Rev 93(5):1449–1475CrossRef
30.
Andersson M, Hedesström M, Gärling T (2014) A social-psychological perspective on herding in stock markets. J Behav Finance 15(3):226–234CrossRef
31.
Cont R, Bouchaud JP (2000) Herd behavior and aggregate fluctuations in financial markets. Macroecon Dyn 4(2):170–196CrossRef
32.
Curtin RT (1982) Indicators of consumer behavior: the University of Michigan surveys of consumers. Public Opin Q 46:340–352CrossRef
33.
Kellstedt PM, Linn S, Hannah AL (2015) The usefulness of consumer sentiment: assessing construct and measurement. Public Opin Q 79(1):181–203CrossRef
34.
35.
Friedman JH (1991) Multivariate adaptive regression splines. Ann Stat 19(1):1–67
36.
Sephton P, Mann J (2013a) Further evidence of the environmental Kuznets curve in Spain. Energy Econ 36:177–181CrossRef
37.
Sephton P, Mann J (2013b) Threshold cointegration: model selection and an application. J Econ Econom 56(2):54–77
38.
Kander A, Lindmark M (2004) Energy consumption, pollutants emissions and growth in the long run: Sweden through 200 years. Eur Rev Econ Hist 8:297–335CrossRef
39.
Lindmark M, Acar S (2014) The environmental Kuznets curve and the Pasteur effect: environmental costs in Sweden 1850–2000. Eur Rev Econ Hist 18(3):306–323CrossRef
40.
Sephton P (1994) Cointegration tests on MARS. Comput Econ 7(1):23–35
41.
Meijer E, Wansbeek TJ (2000) Measurement error in a single regressor. Econ Lett 69:277–284CrossRef
42.
43.
Wansbeek TJ, Meijer E (2000) Measurement error and latent variables in econometrics. North-Holland, Amsterdam
44.
Buonaccorsi J (2010) Measurement error, models, methods, and applications. Chapman & Hall, Boca RatonCrossRef
45.
Meijer E, Wansbeek TJ (2007) The sample selection model from a method of moments perspective. Econ Rev 26:25–51CrossRef
46.
Baltagi BH (2005) Econometric analysis of panel data, 3rd edn. Wiley, New York
47.
Meijer E, Spierdijk L, Wansbeek TJ (2015) Measurement error in panel data. In: Baltagi BH (ed) The Oxford handbook of panel data. Oxford University Press, Oxford, pp 325–362CrossRef
48.
Meijer E, Spierdijk L, Wansbeek TJ (2017) Consistent estimation of linear panel data models with measurement error. J Econ 200:169–180CrossRef
49.
Oczkowski E (2001) Hedonic wine price functions and measurement error. Ecoc Rec 77:374–382CrossRef
50.
Kräger H, Kugler P (1993) Non-linearities in foreign exchange markets: a different perspective. J Int Money Finance 12(2):195–208CrossRef
51.
Beaudry P, Koop G (1993) Do recessions permanently change output? J Monet Econ 31(2):149–163CrossRef
52.
Pfann GA, Schotman PC, Tschernig R (1996) Nonlinear interest rate dynamics and implications for the term structure. J Econom 74(1):149–176CrossRef
53.
Hamilton JD (1996) This is what happened to the oil price–macroeconomy relationship. J Monet Econ 38(2):215–220CrossRef
54.
55.
Narayan PK (2006) The behaviour of US stock prices: evidence from a threshold autoregressive model. Math Comput Simul 71(2):103–108CrossRef
56.
Hansen BE (2011) Threshold autoregression in economics. Stat Interface 4(2):123–127
57.
Koop G, Potter SM (1999) Dynamic asymmetries in US unemployment. J Bus Econ Stat 17(3):298–312
58.
Hansen BE (2017) Regression kink with an unknown threshold. J Bus Econ Stat 35(2):228–240CrossRef
59.
Humpe A, Macmillan P (2009) Can macroeconomic variables explain long-term stock market movements? a comparison of the US and Japan. Appl Financ Econ 19(2):111–119CrossRef
60.
Hansen BE (2000) Sample splitting and threshold estimation. Econometrica 68(3):575–603CrossRef
61.
Müller U, Watson M (2016) Measuring uncertainty about long-run predictions. Rev Econ Stud 83(4):1711–1740CrossRef
62.
Zhou Z, Xu Z, Wu WB (2010) Long-term prediction intervals of time series. IEEE Trans Inform Theory 56(3):1436–1446CrossRef
63.
Pascual L, Romo J, Ruiz E (2006) Bootstrap prediction for returns and volatilities in GARCH models. Comput Stat Data Anal 50(9):2293–2312CrossRef
64.
Pascual L, Romo J, Ruiz E (2004) Bootstrap predictive inference for ARIMA processes. J Time Ser Anal 25(4):449–465CrossRef
65.
Elliott G, Muller UK, Watson MW (2015) Nearly optimal tests when a nuisance parameter is present under the null hypothesis. Econometrica 83(2):771–811CrossRef
66.
67.
Antonopoulos, A. M. (2014). Mastering Bitcoin: Unlocking digital cryptocurrencies. Newton: O’Reilly Media, Inc.
68.
Franco, P. (2014). Understanding Bitcoin: Cryptography, engineering and economics. Oxford: Wiley.CrossRef
69.
70.
71.
Koop, G., Poirier, D. J., and Tobias, J. L. (2007). Bayesian econometric methods. Cambridge: Cambridge University Press.CrossRef
72.
Wold, S., C. Albano, W. J. Dunn III, K. Esbensen, S. Hellberg, E. Johansson, and H. Sjöström. 1983. Pattern recognition: Finding and using regularities in multivariate data. In Proc. UFOST Conf., Food Research and Data Analysis, ed. J. Martens. Applied Science Publications: London.
73.
Wold, S., H. Martens, and H. Wold. 1983. The multivariate calibration problem in chemistry solved by the PLS method. In Proc. Conf. Matrix Pencils, eds. A. Ruhe, and B. Kagstrom, 286–293. Berlin: Springer.
74.
Durbin, J. 1954. Errors in variables. Review of the International Statistical Institute 22: 23–32.
75.
Olkin, I., and S. Yitzhaki. 1992. Gini regression analysis. International Statistical Review 602: 185–196.CrossRef
76.
Fix, Evelyn. 1949. Distributions which lead to linear regressions. In Proceedings of the Berkeley Symposium on Mathematical Statistics and Probability, University of California Press, 79–91.
77.
Rao, C.R. 1949. A correction to note on a problem of Ragnar Frisch. Econometrica 17 (3–4): 212.CrossRef
78.
Rao, C.R. 1947. Note on a problem of Ragnar Frisch. Econometrica 15 (3): 245–249.CrossRef
79.
Rao, C.R. 1966. Characterisation of the distribution of random variables in linear structural relations. Sankhya 28: 251–260.
80.
Rao, C.R. 1952. Advanced statistical methods in biometric research. New York: Wiley.
81.
Rao, C.R. 1973. Linear statistical inference and its applications. New York: Wiley.CrossRef
82.
Reiersol, Olav. 1941. Confluence analysis by means of lag moments and other methods of confluence analysis. Econometrica 9 (1): 1–22.CrossRef
83.
Kagan, A.M., Yu.V. Linnik, and C.R. Rao. 1973. Characterization problems in mathematical statistics. New York: Wiley.
84.
Vinod, H.D. 1982. Maximum entropy measurement error estimates of singular covariance matrices in undersized samples. Journal of Econometrics 20 (1982): 163–174.CrossRef
85.
Neyman, J., and E. Scott. 1948. Consistent estimates based on partially consistent observations. Econometrica 16 (1): 1–32.CrossRef
86.
Goldsmith RW (1969) Financial structure and development. Yale University Press, New Haven
87.
McKinnon RI (1973) Money and capital in economic development. J Int Econ 4:223–224
88.
King RG, Levine R (1993) Finance, entrepreneurship, and growth: theory and evidence. J Monet Econ 32:513–542CrossRef
89.
Destefanis S, Barra C, Lubrano-Lavadera G (2014) Financial development and economic growth: evidence from highly disaggregated Italian data. Appl Financ Econ 24(24):1605–1615CrossRef
90.
91.
Roodman D (2009) How to Do xtabond2: an Introduction to “Difference” and “System” GMM in Stata. Stata Journal 9(1):86–136CrossRef
92.
Aspachs O et al (2007) Towards a measure of financial fragility. Ann Financ 3:37–74CrossRef
93.
Enowbi-Batuo M, Kupukile M (2010) How can economic and political liberalisation improve financial development in African countries? J Financ Econ Pol 2(1):35–59CrossRef
94.
Jokipii T, Monnin P (2013) The impact of banking sector stability on the real economy. J Int Money Financ 32:1–16CrossRef
95.
Creel J, Hubert P, Labondance F (2015) Financial stability and economic performance. Econ Model 48(25):40
96.
Engle RF, Lilien D, Robins R (1987) Estimating time varying risk premia in the term structure: the ARCH-M model. Econometrica 55:391–407CrossRef
97.
98.
Vinod, H.D., and B.D. McCullough. 2003. Comments: Econometrics and software. Journal of Economic Perspectives 17 (1): 223–224.CrossRef
99.
Rao, C. R. 1991. An Autobiographical Account of Research Work, Montreal, Quebec, Canada, H3G 1M6: T. D. Dwivedi, Statistics ’91 Canada, Concordia University.
100.
101.
Hall, W.J., and D.J. Mathiason. 1990. On Large-Sample Estimation and Testing in Parametric Models. International Statistical Review 58 (1): 77–97.CrossRef
102.
Vinod, H.D. 1991. Rao’s Weighted Distribution in Econometrics: An Application to Unemployment Statistics and Okun’s Law. Journal of Quantitative Economics, New Series 7 (2): 247–254.
103.
Kagan, A.M., YuV Linnik, and C.R. Rao. 1973. Characterization Problems in Mathematical Statistics. New York: Wiley.
104.
Yuan M, Lin Y (2006) Model selection and estimation in regression with grouped variables. J R Stat Soc Ser B 68(1):49–67CrossRef
105.
Meier L, van de Geer S, Buhlmann P (2008) The grouped lasso for logistic regression. J R Stat Soc Ser B 70(1):53–71CrossRef
106.
Simon N, Friedman J, Hastie T, Tibshirani R (2013) A sparse-group lasso. J Comput Graph Stat 22(2):231–245CrossRef
107.
Vincent M, Hansen NR (2014) Sparse group lasso and high dimensional multinomial classification. Comput Stat Data Anal 71:771–786CrossRef
108.
Haile PA, Hong H, Shum M (2003) Nonparametric tests for common values in first-price sealed-bid auctions. In: NBER working paper no. 10105
109.
Athey S, Haile PA (2007) Nonparametric approaches to auctions. In: Chapter 60 in handbook of econometrics. Elsevier, Amsterdam
110.
Lokhorst J (1999) The lasso and generalized linear models. Technical report. University of Adelaide, Adelaide
111.
Roth V (2004) The generalized LASSO. IEEE Trans Neural Netw 15(1):16–28CrossRef
112.
Kumar, A. 1993. The Missing Dimension of Macro Economic Policy Making in India. The Black Economy, mimeo. Working Paper of the DSA, Centre for Economic Studies and Planning. New Delhi: School of Social Sciences, Jawaharlal Nehru University.
113.
Rakshit, M. 1989. Underdevelopment of Commodity, Credit and Land Markets: Some Macroeconomic Implications. In Studies in the Macroeconomics of Developing Countries, ed. Mihir Rakshit. Delhi: Oxford University Press.
114.
Perron, P. 1989. The Great Crash, the Oil Price Shock, and the Unit Root Hypothesis. Econometrica 57 (6): 1361–1401.CrossRef
115.
Chudik, A., and M. Hashem Pesaran. 2015b. Common correlated effects estimation of heterogeneous dynamic panel data models with weakly exogenous regressors. Journal of Econometrics 188: 393–420.CrossRef
116.
Chudik, A., K. Mohaddes, Pesaran M. Hashem, and M. Raissi. 2017. Is There a debt-threshold effect on output growth?. Review of Economics and Statistics 99 (1): 135–150.CrossRef
117.
Branson, William, Hannu Halttunen, and Paul Masson. 1977. Exchange rates in the short run: the dollar-deutschemark rate. European Economic Review 10: 303–324.
118.
Hashem, Pesaran M. 2006. Estimation and Inference in large heterogeneous panels with a multifactor error structure. Econometrica, Econometric society 74 (4): 967–1012.
119.
Chudlik A., G. Kapetanios, and Pesaran M. Hashem. 2016. A one-covariate at a time, multiple testing approach to variable selection in high-dimensional linear regression models. Globalization and Monetary Policy Institute Working Paper 290, Federal Reserve Bank of Dallas.
120.
Bahmani-Oskooee, M., and A.B.M. Nasir. 2002. Corruption, law and order, bureaucracy, and real exchange rate. Economic Development and Cultural Change 50: 1021–1028.CrossRef
121.
Pelzman, Joseph. 1984. The multifiber arrangement and its effect on the profit performance of the U.S. textile industry. In The structure and evolution of recent U.S. trade policy, ed. R.E. Baldwin and Anne O. Krueger, 111–141. USA: The University of Chicago Press.
122.
Mishra, P. 2010. Structure, conduct and performance in Indian pharmaceutical industry: a simultaneous equations investigation. Review of Development and Change 15 (1): 69–99.CrossRef
123.
Mishra, Pulak, and Deepti Sahoo. 2012. Structure, conduct and performance of Indian banking sector. Review of Economic Perspectives 12 (4): 235–264.CrossRef
124.
Bhandari, A.K. 2010. Concentration, entry barriers and profitability in the Indian industries: an empirical analysis. Journal of Quantitative Economics 8 (2): 61–80.
125.
Kambhampati, Uma, and Ashok Parikh. 2003. Disciplining firms: the impact of trade reforms on profit margins in Indian industry. Applied Economics, Taylor & Francis Journals 35 (4): 461–470.
126.
127.
Stigler, George J., 1964, A theory of oligopoly, Journal of Political Economy 72, 4461. Reprinted in George J. Stigler, 1968, The organization of industry (Richard D. Irwin, Homewood, IL) 39962
128.
Demsetz, H. 1973. Industry structure, market rivalry and public policy. Journal of Law and Economics 16 (April): 1–9.
129.
Demsetz, H. 1974. Two systems of belief about monopoly’, in industrial concentration: the new learning, The 1974 Conference on Industrial Concentration. In Efficiency, competition, and policy: the organization of economic activity, vol. 2, ed. H.J. Goldschmid, H.M. Mann, and J.F. Weston. Little, Brown.
130.
Peltzman, S. 1977. The gains and losses from industrial concentration. Journal of Law and Economics 20 (October): 229–263.CrossRef
131.
Gale, B., and B. Branch. 1982. Concentration versus market share: which determines performance and why does it matter? The Antitrust Bulletin 27 (1): 83–103.CrossRef
132.
133.
Salinger, M.A. 1984. Tobin’s q, unionization and the concentration-profits relationship’. Rand Journal of Economics 15: 159–170.CrossRef
134.
Lindenberg, E.B., and S.A. Ross. 1981. Tobin’s q ratio and industrial organization’. Journal of Business 54: 1–32.CrossRef
135.
136.
Bothwell, James L., Thomas F. Cooley, and Thomas E. Hall. 1984. A new view of the market structure-performance debate. Journal of Industrial Economics 32 (4): 397–417.CrossRef
137.
Love, I., and L. Zicchino. 2006. Financial development and dynamic investment behavior: evidence from panel VAR. Quarterly Review of Economics and Finance 46: 190–210.CrossRef
138.
Mukhopadhyay, J., and I. Chakraborty. 2017. Competition and industry performance: a panel VAR analysis in Indian manufacturing sector. Journal of Quantitative Economics 15 (2): 343–366.CrossRef
Metadaten
Titel
Einführung und Überblick
verfasst von
Vaibhavi Aher
Copyright-Jahr
2023
Buch
Statistische und mathematische Methoden in der Wirtschaft

Print ISBN: 978-3-658-39274-1

Electronic ISBN: 978-3-658-39275-8

Copyright-Jahr: 2023

DOI
https://doi.org/10.1007/978-3-658-39275-8_1