Translog Gewinn Funktion In Stata Forex

Egwald Wirtschaft: Mikroökonomie Egwalds populäre Web-Seiten werden ohne Kosten für die Nutzer bereitgestellt. Bitte zeigen Sie Ihre Unterstützung durch den Beitritt von Egwald Web Services als Facebook-Fan: Folgen Sie Elmer Wiens auf Twitter: Mit den Cobb-Douglas - und CES-Produktionsfunktionen habe ich eine explizite Kostenfunktion, Gesamtkosten in Abhängigkeit von q, wL, wK und WM, durch Minimierung der Herstellungskosten eines gegebenen Ausgangswertes. Weil die Translog-Produktionsfunktion viel allgemeiner ist (sie hat eine flexible Funktionsform, die es erlaubt, daß die partiellen Elastizitäten der Substitution zwischen den Eingängen variieren), wird die numerische Analyse verwendet, um die Kostenfunktionen zu erhalten, die mit einer gegebenen Translog-Produktionsfunktion verbunden sind. C. Translog (Transcendental Logarithmic) Produktionsfunktion Die dreifaktive Translog-Produktionsfunktion ist: ln (A) aLn (L) aKln (K) aMln (M) bLLn (L) ln (L) bKKln (K) ln (K) bMMn (M) ln (M) bLKln (L) ln (K) bLMln (L) ln (M) bKMln (K) ln (M) f (L, K, M). Wo L Arbeit, K Hauptstadt, M Materialien und Lieferungen, und q Produkt. I. Um Schätzungen der Translog-Produktionsfunktion zu erhalten, verwenden wir die CES-Produktionsfunktion, um eine Sequenz von Beobachtungen zu erzeugen, die die CES-Kleinstfaktoreingaben zu Faktorpreisen und Produktionsniveaus betrifft. Die dreifache CES-Produktionsfunktion ist: q ein Alpha (L-rho) beta (K-rho) gamma (M-rho) (-nurho), wobei L Arbeit, K Kapital, M Materialien und Lieferungen und q Produkt. Der Parameter nu ist ein Maß für die Skaleneffekte, während der Parameter rho die Elastizität der Substitution liefert: sigma 1 (1 rho). Die geschätzten Koeffizienten der Translog-Produktions - und Kostenfunktionen variieren mit den Parametern sigma, nu, alpha, beta und gamma der CES-Produktionsfunktion. Setzen Sie die unten stehenden Parameter für die erneute Ausführung mit Ihren eigenen CES-Parametern. Beschränkungen. 7 1 8594 Eingaben substituiert Die CES-Produktionsfunktion wie angegeben: q 1 0,35 (L - 0,167647) 0,4 (K - 0,167647) 0,25 (M - 0,167647) (-10,167647) II. Die Schätzung der Translog-Produktionsfunktion unter Verwendung mehrfacher Regression ergab die folgenden Koeffizientenschätzungen: lnA 6.0E-6 aL 0.349891 aK 0.399994 aM 0.250116 bLL -0.019666 bKK -0.021337 bMM -0.016437 bLK 0.024565 bLM 0.014766 bKM 0.018108 aL aK aM 1 2 bLL bLK bLM 0 2 BKK bLK bKM 0 2 bMM bLM bKM 0 Die geschätzte Translog-Produktionsfunktion: ln (q) 6.0E-6 0.349891 ln (L) 0.399994 ln (K) 0.250116 ln (M) -0.019666 ln (L) ln (L) -0.021337 (K) ln (K) -0,016437 ln (M) ln (M) 0,024565 ln (L) ln (K) 0,014766 ln (K) ln (M) f (L, K) , M). Elastizität des Produktionsmaßstabes: Langer Lauf: Kapitalvariable: 949 LKM 949 (L, K, M) aL aK aM (2bLL bLK bLM) ln (L) (2bKK bLK bKM) ln (K) (2bMM bLM bKM) M). Kurzfassung: Captial K K: 949 L K M 949 (L, K, M) aL aM (2bLL bLM) ln (L) (bLK bKM) ln (K) (2bMM bLM) ln (M). Die Translog-Produktionsfunktion q F (L, K, M) exp (f (L, K, M)) ist konkav zum Ursprung des dreidimensionalen Raums, wenn sein Hessian negativ ist Halb) bestimmt. Definieren Sie die Matrizen h 1. H 2. Und h 3. Der Hessische von F (L, K, M) ist negativ, wenn die Determinanten h 1, h 2 und h 3 im Zeichen abwechseln, beginnend mit negativ. Wenn eine oder mehrere Determinanten einen Nullwert haben, dann ist der Hessen von F (L, K, M) negativ semidefinit und F (L, K, M) ist quasi-konkav zum Ursprung des dreidimensionalen Raumes von (L, K, M). Die Krümmung der geschätzten Translog-Produktionsfunktion hängt von der Elastizität der Substitution, Sigma, der CES-Produktionsfunktion ab. (L, K, M) ist nicht konkav zum Ursprung des dreidimensionalen Raumes von (L, K, M), sigma 1 nu 1 8594 F (L, K, M) ist konkav zum Ursprung Des dreidimensionalen Raumes von (L, K, M), Überprüfen Sie die angezeigten Krümmungsbedingungen auf andere Werte von sigma, nu, alpha, beta und gamma. III. Least-Cost-Kombination von Inputs Der Unternehmer, das Management und die Mitarbeiter des Profitmaximierungsunternehmens wählen die Faktoranteile und - größen sowie die Produktionsniveaus unter Berücksichtigung der Faktoreinnahmen und Produkte. Für jede angegebene Kombination von positiven Faktorpreisen wL, wK und wM wird die Kombination der Faktoreingaben L, K und M die Kosten der Erzeugung eines beliebigen positiven Ausgangssignals minimieren, q Äquivalent: Die Werte von L finden , K, M, und Mikro, die die Lagrange-Funktion minimieren, wenn die Faktorpreise wl, wK und wM: G (qL, K, M, M), oder äquivalent, die das Lagrange-G (qL, K, M, micro) - G (qL, K, M, micro) maximieren. G (qL, K, M, Mikro) - (wL L wK K wM M) - Mikro q - exp (f (L, K, M)). Erste Ordnung: Um die Gleichungen 0. bis 3. numerisch zu lösen, verwendete ich für gegebene q, wL, wK und wM die Bedingungen erster Ordnung 0. bis 3. und die zugehörigen Jacobian. (L, K, M)): Das Lagrange-G (qL, K, M, micro) erhält ein Maximum bei q, L, K und M, wenn die umgrenzte, hauptsächliche kleinere Determinante H 2 positiv ist und die umgrenzte Determinante H 3 negativ ist. (Siehe nachstehende Tabelle und die mathematischen Anmerkungen.) IV. Lange Laufzeit: Kapitalvariable. Angenommen, die Firma kauft ihre Eingaben zu den Preisen: wL 7 wK 13 nbsp wM 6. Wenn wir das kostengünstigste Problem lösen (und unter Berücksichtigung dieser Kleinstkosten), können wir die CES-Kostendaten mit den geschätzten Translog-Kostendaten vergleichen, wie in der folgenden Tabelle dargestellt. Die Begriffe s LK. S LM. Und s KM die Allen-Teilelastizitäten der Substitution sind. Translog Long-Run-Cost-Daten zurück zur Skala 1, Elastizität der Substitution 0.85 wL 7, wK 13, wM 6 mdash CES-Daten mdash mdash mdash Geschätzte Translog-Daten mdash mdash Die Lagrange-Methode zur Gewinnung der kostengünstigsten Kombination von Eingaben, Lösungsvariablen micro. L, K und M für spezifizierte Werte von q, wL, wK und wM. Das heißt, die Lösungsvariablen sind Funktionen: Mikromikro (q wL, wK, wM), LL (q wL, wK, wM), KK (q wL, wK, wM), M M (q wL, wK, wM). Die Lagrangesche Methode erzeugt auch die Jacobische Matrix (umgrenzte Hessische von G - G) der vier Funktionen, G micro. G L. G K. G M. In Bezug auf die Auswahlvariablen x3BC, L, K und M: Die Jacobi-Matrix der vier Lösungsfunktionen x3A6 micro. L K. M in Bezug auf die Variablen q, wL, wK und wM gleich dem Negativ der Matrixinverse von J 3 ist. Was die Vergleichsstatik der Lösungsfunktionen ergibt. Zum Beispiel sind bei q 30, wL 7, wK 13 und nbsp wM 6: Die Uzawa-Teilelastizitäten der Substitution bei denselben Werten von q, wL, wK und wM: Der Faktor erfordert Elastizitäten bei denselben Werten von q, wL , WK und wM: wobei beispielsweise epsilon L, wK partln (L (q wL, wK, wM)) partln (wK) (partln (L (q wL, wK, wM) Die Kostenfunktion C (qwL, wK, wM) ist ein konkaver Faktor-Faktor. Die Kostenfunktion C (qwL, wK, wM) Wenn die Hessische Matrix 8711 2 ww C (qwL, wK, wM) partieller Ableitungen zweiter Ordnung in Bezug auf Faktorkosten negativ semidefinit ist. Die Matrix 8711 2 ww C (qwL, wK, wM) ist negativ semidefinit, wenn ihre Eigenwerte nichtpositiv sind. Die Eigenwerte von 8711 2 ww C sind e1 -4.4778, e2 -2.7932 und e3 0. V. Kurzer Verlauf: Kapitalfest: K K 24.41. Lassen Sie das Unternehmen seine Eingänge zu den gleichen Preisen kaufen: wL 7 wK 13 nbsp wM 6. Stellen Sie das Kapital auf der niedrigsten Kostenebene für q 30 ein. Lösen Sie das kostengünstigste Problem, das Kapital fest hält, können wir die kurzfristigen Vergleiche vergleichen CES-Kostendaten mit den geschätzten Translog-Short-Run-Cost-Daten, wie in der folgenden Tabelle dargestellt. Die Lagrange-G (qL, K, M, micro) erhält ein Maximum bei q, L, K. Und M, wenn die umgrenzte Determinante H 2 positiv ist. Die Translog-Produktionsfunktion F (L, K, M) ist konkav zum Ursprung des 2-dimensionalen Raumes (L, M), wenn h 1 0. (Siehe nachstehende Tabelle und die mathematischen Anmerkungen) Translog Short Run Cost Daten zurück zur Skala 1, Elastizität der Substitution 0.85 wL 7, wK 13, wM 6 K 24.41 mdash CES Daten mdash mdash mdash Geschätzte Translog Daten mdash mdash Wir erhalten eine U-förmige, kurzfristige durchschnittliche Kostenkurve, mit Kapital fixiert. Die kurzfristige Durchschnittskostenkurve ist (ca.) tangential zur langfristigen Durchschnittskostenkurve bei q 30. Die Elastizität der Skala, 949 LKM. Ist entlang der kurzfristigen Durchschnittskostenkurve konstant und entspricht der Langzeit-Elastizität der Skala, 949 LKM. Die Kurzzeit-Elastizität der Skala mit dem bei K 24.41 fixierten Kapital ist eine abnehmende Funktion entlang der kurzfristigen Durchschnittskostenkurve, da sigma kleiner als 1 ist. Hier habe ich zwei Maßnahmen der Kurzstreckenelastizität der Substitution zwischen L und M aufgeführt Das 3-Faktor-Maß von s LM verwendet die Allen-Teilelastizität der Substitutionsformel. Das 2-Faktor-Maß von s LM verwendet die Standard-Short-Run-Formel, die davon ausgeht, dass nur L und M mit dem Ausgang variieren können, mit einer festen Menge an Kapital vorhanden. Eine andere Möglichkeit wäre, eine Zwei-Faktor-Produktionsfunktion q F (L, M) abzuschätzen und dann s LM zu berechnen. Dann ist das Kapital K eine fehlende Variable aus der Schätzung, die die Schätzungen der Koeffizienten der Produktionsfunktion F verschiebt. Die Lagrange-Methode zur Gewinnung der kostengünstigsten Kombination von Inputs liefert Werte für die Lösungsvariablen micro. L und M für spezifizierte Werte von q, wL, wK und wM. Das heißt, die Lösungsvariablen sind Funktionen: Mikromikro (q wL, wK, wM), LL (q wL, wK, wM), M M (q wL, wK, wM). Die Lagrangesche Methode erzeugt auch die Jacobische Matrix (umgrenzte Hessische von G - G) der drei Funktionen, G micro. G L. G M. In Bezug auf die Wahlvariablen x3BC, L und M: Die Jacobi-Matrix der drei Lösungsfunktionen x3A6 micro. L M in Bezug auf die Variablen q, wL, wK und wM dem Negativ der Matrix invers von J 2 entspricht. Was die Vergleichsstatik der Lösungsfunktionen ergibt. Beispielsweise sind bei q 30, KK 24.41, wL 7, wK 13 und nbsp wM 6: Die Faktorbedarfselastizitäten bei q 30, wL 7, wK 13 und nbsp wM 6. wo zum Beispiel epsilon L, wM partln (W (wM, wM, wM))) (partieller Wert (wM) (Ww, wK, wM) ist eine konkave Faktorpreise, wenn die hessische Matrix 8711 2 ww C (qwL, wK, wM, wK, wM) ) Partieller Ableitungen zweiter Ordnung in Bezug auf Faktorkosten negativ semidefinit ist. Die Matrix 8711 2 ww C (qwL, wK, wM) ist negativ semidefinit, wenn ihre Eigenwerte nichtpositiv sind. Die Eigenwerte von 8711 2 ww C sind e1 -4.4764 und e2 0. Grafik der durchschnittlichen Kosten und Grenzkosten Translog Kosten Produktionsfunktionen - Capital Fixed Average Kostenfunktion Grenzkostenfunktion L. R. Durchschnittliche Kostenfunktion VI. Lange Laufzeit: Kapitalvariable. Lassen Sie uns den Preis von M, Materialien und Zubehör zu erhöhen. Nun kauft die Firma ihre Inputs zu den Preisen: wL 7 wK 13 nbsp wM 7. Wenn wir das kostengünstigste Problem lösen (und unter Berücksichtigung dieser Kleinstkosten), können wir die CES-Kostendaten mit den geschätzten Translog-Kostendaten vergleichen, wie in der folgenden Tabelle dargestellt. Die Begriffe s LK. S LM. Und s KM die Allen-Teilelastizitäten der Substitution sind. Translog Long Run Cost Daten Zurück zur Skala 1, Elastizität der Substitution 0,85 wL 7, wK 13, wM 7 VII. Kurzfassung: Kapital Fixed: K K 25.23. Lassen Sie das Unternehmen seine Eingänge zu den gleichen (wM erhöhten) Preisen kaufen: wL 7 wK 13 nbsp wM 7. Setzen Sie das Niveau des Kapitals auf die niedrigste Kostenebene für q 30: dann. Wenn wir das kostengünstigste Problem mit dem festgehaltenen Kapital lösen, können wir die kurzfristigen CES-Kostendaten mit den geschätzten Translog-Kurzzeitkosten vergleichen, wie in der folgenden Tabelle dargestellt. (Siehe die Diskussion der Kurzzeit-Elastizität der Substitution, s LM.) Translog Kurzlauf-Kostendaten Rückkehr zur Skala 1, Elastizität der Substitution 0.85 wL 7, wK 13, wM 7 K 25.23 mdash CES Daten mdash mdash mdash Geschätzt Translog Data mdash mdash Wir erhalten eine U-förmige, kurzfristige durchschnittliche Kostenkurve, mit Kapital fixiert. Die kurzfristige Durchschnittskostenkurve ist (ca.) tangential zur langfristigen Durchschnittskostenkurve bei q 30. Die Elastizität der Skala, 949 LKM. Ist entlang der kurzfristigen Durchschnittskostenkurve konstant und entspricht der Langzeit-Elastizität der Skala, 949 LKM. Die kurzfristige Elastizität der Skala mit dem auf K 25.23 fixierten Kapital ist eine abnehmende Funktion entlang der kurzfristigen Durchschnittskostenkurve, da Sigma kleiner als 1 ist. Graph der Durchschnittskosten und Grenzkosten Translog Kosten Produktionsfunktionen - Kapital Fix Durchschnittliche Kostenfunktion Grenzkosten Funktion LR Durchschnittliche Kostenfunktion Ein gegebener Ausgangswert q q. Kann durch verschiedene Kombinationen von Faktoreingängen L, K und M erzeugt werden. Festlegung des Produktausgangsniveaus bei q q. Erhalten wir eine Gleichung aus der Translog-Produktionsfunktion: ln (q) ln (A) aLln (L) aKln (K) aMln (M) bLLln (L) ln (L) bKKln (K) (M) bLKln (L) ln (K) bLMln (L) ln (M) bKMln (K) ln (M) f (L, K, M). Für die dreidimensionale isoquante Fläche, wenn q q. Die Isoquantenfläche ist tangential zur Isokoordinatenebene: C (q) wL L wK K wM M auf der kostenminimierenden Kombination von Faktoreingängen (L, K, M) (L. K.M). Man betrachte die Translog-Produktionsfunktion wie folgt: ln (q) 6.0E-6 0.349891 ln (L) 0.399994 ln (K) 0.250116 ln (M) -0.019666 ln (L) ln (L) -0.021337 ln (K) K) -0,016437 ln (M) ln (M) 0,024565 ln (L) ln (K) 0,017766 ln (K) ln (M) Wenn q 30 und (wL, wK, wM) (7, 13, 6) die Kostenminimierungseingaben sind: C (30) 7 36,89 13 24,41 6 31,59 765,17. Wenn wir die Translog-Gleichung für L, K und M nacheinander lösen, erhalten wir drei Gleichungen für die dreidimensionale Isoquantenoberfläche. Durch Fixieren der Eingangsgröße für einen Faktor in diesen Gleichungen erhalten wir drei zweidimensionale Isoquantenkurven. Betrachten Sie zuerst das L-K Isoquant. Set M M. (L) log (L) log log (L) log log (L) log log (L) log log (M) - bMM log (M) log (M) - bLM log (L) log (M). Das L-K-Isoquant, ausgedrückt als K als Funktion von L: K exp ((-b sqrt (bb4ac)) (2a)). Zweitens betrachten die L-M Isoquant. Set K K. (L) log (L) - log (L) - log (A) - aL log (L) - aK log (K) - bLL log (L) - bKK log (K) log (K) - bLK log (L) log (K). Das L-M-Isoquant, ausgedrückt als M als Funktion von L: M exp ((-b sqrt (bb4ac)) (2a)). Die folgenden Diagramme zeigen in blau die L-K - und L-M-Isoquanten für q 24, 30 und 36. Die gelben Linien stellen die Isocostlinien dar. Kombinationen von L, K und M, die zu konstanten Gesamtkosten zu den Preisen wL 7, wK 13 und wM 6 erworben werden können. Die Steigung einer LK-Isocostlinie ist m K - wL wK -7 13 die Steigung von a LM-Isocostlinie ist m M - wL wM-7 6. Für q 30 weist die LK-Isocostlinie einen K-Intercept bei (C (30) - wM M) wK (765.17 - 6 31.59) 13 44.28 auf, während der LM-Isocost Linie hat einen M-Schnittpunkt bei (C (30) - wK K) wM (765,17 - 13 24,41) 6 74,63. Für q 30 ist das L-K-Isoquant tangential zur L-K-Isocostlinie bei (L. K) (36.89, 24.41), während das L-M-Isoquant tangential zur L-M-Isocostlinie bei (L. M) (36.89, 31.59) ist. Der Hessische von F (L, K, M) ist negativ, wenn die Determinanten h 1, h 2 und h 3 abwechselnd im Zeichen, beginnend mit negativ, auftreten. Wenn eine oder mehrere Determinanten einen Nullwert haben, dann ist der Hessen von F (L, K, M) negativ semidefinit und F (L, K, M) ist quasi-konkav zum Ursprung des dreidimensionalen Raumes von (L, K, M). II. Die partiellen Ableitungen von f (L, K, M) fL (L, K, M) (1L) aL 2 bLL ln (L) bLK ln (K) bLM ln (M) (1L) vL, (M) (1K) aM 2 bMM ln (M) bLM (M) (1K) vK, fM (L, K, M) (1K) Ln (L) bKM ln (K) (1M) vM, III. Die am wenigsten kostengünstige Kombination von Inputs: Finden Sie die Werte von L, K, M und Micro, die die Lagrange-Funktion minimieren, wenn die Faktorpreise wL, wK und wM: G (qL, K, M, micro) wL L wK K sind (QL, K, M, micro) - G (qL, K, M, m)) oder gleichermaßen maximieren. G (qL, K, M, Mikro) - (wL L wK K wM M) - Mikro q - exp (f (L, K, M)). Erste Auftragsbedingungen: IV. Die am wenigsten kostengünstige Kombination von Inputs: Capital fixed: Mit dem Wert des Kapitalwertes fixiert auf K K. Die Werte von L, M und Micro zu minimieren, die die Lagrangeschwingung minimieren, wenn die Faktorpreise wl, wK und wM: G (qL, K, M, mikro) wL L wK K wM M micro q - exp (f (L , K, M)) oder äquivalent, die das Lagrange-G (qL, K, M, micro) - G (qL, K, M, micro) maximieren. Erste Auftragsbedingungen: K K Jacobian zweiter Auftragsbedingungen: K K. (L, K, M) exp (f (L, K, M)): V. Allen partielle Elastizität der Substitution Schreiben der Produktionsfunktion als q F (L, K, M), lassen Sie die eingegrenzten Hessian sei: Wenn F die Determinante des umgrenzten Hessischen ist und F LK der mit F LK assoziierte Kofaktor ist. Dann ist die Allenelastizität der Substitution definiert als: VI. Zwei Faktorelastizität der Substitution Die Produktionsfunktion ist q F (L, K, M), wobei K unterstrichen ist, um anzuzeigen, dass es kurzzeitig konstant ist. 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Angesichts der wirtschaftlichen und geographischen Eigenschaften eines Ortes kann man die wahrscheinlichen Handelsaktivitäten abschätzen, die als Indikator für das relative wirtschaftliche Potential der Gebiete dienen können. Allerdings sind die Handelsschätzungen nur auf regionaler Ebene der Disaggregation verfügbar, obwohl die Planung von lokalen Regierungen und sogar von Linienstellen der Zentralregierung hauptsächlich auf subregionaler Ebene geschieht. In dieser Forschung füllen wir diese Datenlücke, indem wir den Handel auf Stadt - oder Stadtebene über ein Gravitationsmodell des Handels abschätzen. Normalerweise wird der subregionale Handel mit der Ordinary Least Regression geschätzt, aber diese Forschung nutzt Poisson Regression, die besser ist, Nullhandelswerte ohne Transformation zu behandeln. Die Forschungsergebnisse wurden von einer Reihe von Regierungsbehörden in ihren jeweiligen Programmen von Nikkin Beronilla Patrocinio angewendet. 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Ledenyov, Viktor O. 2013 Bayesian Approach and Identification by Kociecki, Andrzej 2013 Education and Economic Growth: A Meta-Regression Analysis by Benos, Nikos Zotou, Stefania 2013 Inference in non stationary asymmetric garch models by Francq, Christian Zakoian, Jean-Michel 2013 Does Okuns Law state a Pi:1 ratio Toward a harmonic interpretation of why Okuns Law works by Albers, Scott Albers, Andrew L. 2013 Of Jane Austen and the secret life of econometric quantities, or as otherwise entitled on Okuns Law and the multiplicative inverse surprise by Albers, Scott 2013 Alternative inflation hedging strategies for ALM by Fulli-Lemaire, Nicolas 2013 Modeling Voting Behavior in the Eurovision Song Contest by Dogru, Blent 2013 The neglected heterogeneity of spatial agglomeration and co-location patterns of creative employment: evidence from Portugal by Sara Santos Cruz Aurora A. C. Teixeira 2013 Redefining The Modifiable Areal Unit Problem Within Spatial Econometrics, The Case Of The Scale Problem by Michal Bernard Pietrzak 2013 Modeling and Estimating Volatility of Options on Standard Poors 500 Index by Boleslaw Borkowski Monika Krawiec Yochanan Shachmurove 2013 Martingale unobserved component models by Neil Shephard 2013 The Restricted Least Squares Stein-Rule in gretl by Lee C. Adkins 2013 Martingale unobserved component models by Neil Shephard 2013 Endogenous Stratification in Randomized Experiments by Alberto Abadie Matthew M. Chingos Martin R. West 2013 Why ask Why Forward Causal Inference and Reverse Causal Questions by Andrew Gelman Guido Imbens 2013 Unobservable Selection and Coefficient Stability: Theory and Validation by Emily Oster 2013 Estimating the Impact of Means-tested Subsidies under Treatment Externalities with Application to Anti-Malarial Bednets by Debopam Bhattacharya Pascaline Dupas Shin Kanaya 2013 Behavioral Law and Economics: Empirical Methods by Christoph Engel 2013 Pauvret montaire versus non-montaire au Burundi by Jean-Claude Nsabimana Nicolas Ndayishimiye Christian Kwidera Aurlien Beko 2013 An Empirical Analysis of Inflation-Growth Nexus in Developing Countries: The Case of Sri Lanka by Nawalage S. Cooray 2013 Inference in ordered response games with complete information by Andres Aradillas-Lopez Adam Rosen 2013 Estimating demand for differentiated products with error in market shares by Amit Gandhi Zhentong Lu Xiaoxia Shi 2013 Specification tests for partially identified models defined by moment inequalities by Federico Bugni Ivan A. Canay Xiaoxia Shi 2013 A simple but efficient approach to the analysis of multilevel data by Bache, Stefan Holst Milton Kristensen, Troels 2013 The Dutch Disease in the Portuguese Economy by Joo Sousa Andrade Antnio Portugal Duarte 2013 Through the Looking Glass: Indirect Inference via Simple Equilibria by Calvet. Laurent Czellar, Veronika 2013 On the economic effects of public infrastructure investment:A survey of the international evidence by Alfredo Marvo Pereira Jorge M. Andraz 2013 Multiscale Adaptive Inference on Conditional Moment Inequalities by Timothy B. Armstrong Hock Peng Chan 2013 Multiscale Adaptive Inference on Conditional Moment Inequalities by Timothy B. Armstrong Hock Peng Chan 2013 Multiscale Adaptive Inference on Conditional Moment Inequalities by Timothy B. Armstrong Hock Peng Chan 2013 Co-summability from linear to non-linear cointegration by Gonzalo, Jess Berenguer Rico, Vanessa 2013 El sentido de la causalidad entre inversin en capital fsico y crecimiento econmico una evaluacin emprica para la economa colombiana 1970-2010 by Julin Enrique Lpez Siabato 2013 Crecimiento econmico y desempleo: Retos a largo plazo by Mauricio SANTAMARIA SALAMANCA Gabriel PIRAQUIVE GALEANO Gustavo HERNANDEZ DIAZ Norberto ROJAS DELGADILLO 2013 Testing and Estimating Models Using Indirect Inference by Le, Vo Phuong Mai Meenagh, David 2013 Likelihood inference in non-linear term structure models: the importance of the lower bound by Andreasen, Martin Meldrum, Andrew 2013 Nets: Network Estimation for Time Series by Matteo Barigozzi Christian Brownlees 2013 Demand factors that influence financial inclusion in Mexico: analysis of the barriers based on the ENIF survey by Carmen Hoyo Ximena Pena David Tuesta 2013 Factores de demanda que influyen en la Inclusion Financiera en Mexico. 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Yun, Kun-Young 2013 Bridges Over Water:Understanding Transboundary Water Conflict, Negotiation and Cooperation by Ariel Dinar Shlomi Dinar Stephen McCaffrey Daene McKinney 2013 The effect of foreign direct investment on unemployment in Bulgaria by Rosen Nikolaev Viktoria Stancheva 2013 Out of Sample Value-at-Risk and Backtesting with the Standardized Pearson Type-IV Skewed Distribution by Stavros Stavroyiannis Leonidas Zarangas 2013 Purposes and limitations of econometric analysis according to recent approaches by Siro Lombardini 2013 A Real Economic Activity Indicator for Turkey by S. Boragan Aruoba Cagri Sarikaya 2013 Impacts of Inflation on Agricultural Prices: Panel Smooth Transition Regression Analysis by Bulent Guloglu Saban Nazlioglu 2013 Non-linear Regression used in Economic Analysis by Gabriela Victoria ANGHELACHE Constantin ANGHELACHE Andreea Gabriela BALTAC Ligia PRODAN 2013 Non-parametrical Estimation of the Regression used in Economic Analyses by Constantin ANGHELACHE Gabriela Victoria ANGHELACHE Liviu BEGU Georgeta BARDASU 2013 Comparative analysis of the degree of international capital mobility in Tunisia and Morocco: revised Feldstein Horioka approach by Sarra Ben Slimane Moez Ben Tahar Zied Essid 2013 Crecimiento, empleo y productividad en la industria manufacturera mexicana by Liquitaya Briceo, Jos D. 2013 Researching and forecasting aggregated consumers perception of imported food: Russia and Brazil case studies (19922020) by Penikas, Henry Savelyeva, Alina 2013 Sample selection bias as a specification error by Heckman, James 2013 Marital wage gap by Aistov, Andrey 2013 Econometric analysis of the effect of marital status change on wages in Russia by Rodionova, Lilia 2013 Econometric modeling risk of consumer loans by Nivorozhkina, Ludmila Ovcharova, Lilia Sinyavskaya, Tatiana 2013 Human capital estimation in professional football by Polyakov, Konstantin Zhukova, Ludmila 2013 The use of econometric models for long-term policies: A critical view by Luigi Spaventa 2013 Export-led growth in Tunisia: A wavelet filtering based analysis by Hamrita Mohamed Essaied 2013 Migration in the EU - Between Brain Drain and Cheap Workforce Transfer by Burciu Andreea Ardelean Andreea 2013 The Development of Earnings in Romania Before and After the Economic CrisisAbstract:Any economy attaches a significant role to the evolution of the wages in order to determine unemployment and inflation. The rapid increase in the average salary both before and after the emergence of the economic and financial crisis is the reason for this study. This paper is focused on the evolution of nominal and real net salary earnings at the level of the national economy, on economic activities and on development regions and the influence of salary earnings on the inflation rate and on the unemployment rate. The relationships between the salary earnings, the inflation rate and the unemployment rate are studied by means of multifactorial linear regression models. For the analysis of the correlations we took into account a 13-year period, 20002012, and for the evolution of the two studied indicators, the analysed period is 2007 2012. For the econometric modelling we used a software package called Eviews by Neculescu Consuela erbnescu Luminia 2013 A Tale Of Two Cycles In Developing And Advanced Economies: A Country Case Study Comparison by Percic Stanislav Apostoaie Constantin-Marius Chirlesan Dan 2013 Semiparametric Efficiency Bounds for Microeconometric Models: A Survey by Severini, Thomas A. Tripathi, Gautam 2013 Inference in the Presence of Weak Instruments: A Selected Survey by Poskitt, D. S. Skeels, C. L. 2013 On The Economic Effects Of Public Infrastructure Investment: A Survey Of The International Evidence by ALFREDO M. PEREIRA JORGE M. ANDRAZ 2013 Construccin del ndice de Cohesin Social para Mxico: Una propuesta mediante un anlisis de componentes principales by Juan Bacilio Guerrero Juan Alberto Acosta 2013 Is Financial Development a Factor to the Leading Growth Profile of the South African Economy Measuring and Uncovering the Hidden Secret by Abdulkadir Abdulrashid Rafindadi Zarinah Yusof 2013 Impact Of Education On Economic Growth In Mexico, 1990-2008, Impacto De La Educacion En El Crecimiento Economico En Mexico, 1990-2008 by Juan M. Ocegueda Hernandez Juan A. Meza Fregoso C. Domingo Coronado Garca 2013 The Economic Impact Of International Migration On Economic Growth In Mexico, El Efecto Economico De La Migracion Internacional En El Crecimiento Economico De Mexico by Martina Rodriguez Dominguez Emilio Hernandez Gomez 2013 Academic Rankings with RePEc by Christian Zimmermann 2013 Polynomial Regressions and Nonsense Inference by Daniel Ventosa-Santaulria Carlos Vladimir Rodrguez-Caballero 2013 Ranking Leading Econometrics Journals Using Citations Data from ISI and RePEc by Chia-Lin Chang Michael McAleer 2013 The Geometric Meaning of the Notion of Joint Unpredictability of a Bivariate VAR(1) Stochastic Process by Umberto Triacca 2013 Structural Panel VARs by Peter Pedroni 2013 Parametric and Nonparametric Frequentist Model Selection and Model Averaging by Aman Ullah Huansha Wang 2013 Generalized Empirical Likelihood-Based Focused Information Criterion and Model Averaging by Naoya Sueishi 2013 Generalized Spatial Two Stage Least Squares Estimation of Spatial Autoregressive Models with Autoregressive Disturbances in the Presence of Endogenous Regressors and Many Instruments by Fei Jin Lung-fei Lee 2013 Outlier Detection in Regression Using an Iterated One-Step Approximation to the Huber-Skip Estimator by Sren Johansen Bent Nielsen 2013 Constructing U. K. Core Inflation by Terence C. Mills 2013 Forecasting Value-at-Risk Using High-Frequency Information by Huiyu Huang Tae-Hwy Lee 2013 Ten Things You Should Know about the Dynamic Conditional Correlation Representation by Massimiliano Caporin Michael McAleer 2013 On Diagnostic Checking of Vector ARMA-GARCH Models with Gaussian and Student-t Innovations by Yongning Wang Ruey S. Tsay 2013 The financial market effect of FOMC minutes by Rosa, Carlo 2013 Linguistic Diversity and Preferences: Econometric Evidence from European Cities by Laura Onofri Paulo A. L.D. Nunes Jasone Cenoz Durk Gorter 2013 Nonlinear analysis among crude oil prices, stock markets return and macroeconomic variables by Naifar, Nader Al Dohaiman, Mohammed Saleh 2013 Unobserved heterogeneity and risk in wage variance: Does more schooling reduce earnings risk by Mazza, Jacopo van Ophem, Hans Hartog, Joop 2013 Estimating non-linear serial and cross-interdependence between financial assets by Righi, Marcelo Brutti Ceretta, Paulo Sergio 2013 Explaining the unpredictable: An empirical analysis of U. S. patent infringement awards by Mazzeo, Michael J. Hillel, Jonathan Zyontz, Samantha 2013 Energy as a driver of growth in oil exporting countries by Damette, Olivier Seghir, Majda 2013 Biofuel-related price transmission literature: A review by Serra, Teresa Zilberman, David 2013 Fitting semiparametric Markov regime-switching models to electricity spot prices by Eichler, M. Trk, D. 2013 Fuel demand in Brazil in a dynamic panel data approach by Santos, Gervsio F. 2013 A check for finite order VAR representations of DSGE models by Franchi, Massimo Vidotto, Anna 2013 Recursive predictive tests for structural change of long-memory ARFIMA processes with unknown break points by Wang, Shin-Huei Vasilakis, Chrysovalantis 2013 Modelos de prediccin de la fragilidad empresarial: aplicacin al caso colombiano para el ao 2011 by Prez G. Jorge Ivn Gonzlez C. Karen Lorena Lopera C. Mauricio 2013 El problema de la consultora est en la t by Julio Csar Alonso Beatriz Eugenia Gallo 2013 La brecha del producto y el producto potencial en Venezuela: una estimacin SVAR by Pedro Alexander Harmath Fernndez Jos U. Mora Mora Rafael Alexis Acevedo Rueda 2013 Latest Challenges In Efficiency Convergence In Balkan And Baltic Countries by Mihi-Cosmin M. Popovici 2013 Impact Of The Inflation On The Exchange Rate And On The Average Salary by Consuela I. NECULESCU Luminia L. ERBNESCU 2013 Agglomerationsvorteile in der Wissensgesellschaft: Empirische Evidenz fr deutsche Gemeinden by Oliver Falck Stephan Heblich Anne Otto 2013 Do bubbles occur in the gold price An investigation of gold lease rates and Markov Switching models by Brian M. Lucey Fergal A. OConnor 2013 Applied Nonparametric Regression Analysis: the Choice of Generalized Additive Models by Morteza Haghiri 2013 A Research On Employees Perception Of Organizational Justice And Their Propensity To Leave: Case Study Of 4 And 5 Star Hotels In The Province Of Antalya by Assoc. Prof. Sule AYDIN TKELTRK Ph. D Assist. Prof. Fehmi Volkan AKYN 2013 Considerations on the stochastic approach in economics by Ion Smeureanu Gheorghe Ruxanda 2012 Determinants of Firm Innovation - Evidence from German Panel Data by Stefan Kipar 2012 Trkiyede Reel Dviz Kurunun Dorusal Olmayan Ekonometrik Modeller ile ncelenmesi:Band-TAR ve STAR Modelleri by Ozgur Omer ERSN 2012 En busca de un buen marco de referencia predictivo para la inflacin en Chile by Pincheira, Pablo Garca, lvaro 2012 Considerations on partially identified regression models by Cerquera, Daniel Laisney, Franois Ullrich, Hannes 2012 Explaining Variations in Breast Cancer Screening Across European Countries by Wbker, Ansgar 2012 Polynomics telecommunication regulation index 2012 by Zenhaeuserna, Patrick Schneiderb, Yves 2012 Empirical analysis of regional economic performance in Russia: Human capital perspective by Kufenko, Vadim 2012 Validierung von Konzepten zur Messung des Marktrisikos: Insbesondere des Value at Risk und des Expected Shortfall by Mehmke, Fabian Cremers, Heinz Packham, Natalie 2012 Continuous Empirical Characteristic Function Estimation of GARCH Models by Dinghai Xu 2012 GMM Estimation of a Stochastic Volatility Model with Realized Volatility: A Monte Carlo Study by Pierre Chausse Dinghai Xu 2012 Monte Carlo likelihood inference in multivariate model-based geostatistics by Marco Minozzo Clarissa Ferrari 2012 Demandas de turismo Argentina y Brasilea en Uruguay by Silvia Altmark Gabriela Mordecki Florencia Santiaque W. Adrin Risso 2012 Considerations on partially identified regression models by Daniel Cerquera Franois Laisney Hannes Ullrich 2012 A New Structural Break Model with Application to Canadian Inflation Forecasting by John M Maheu Yong Song 2012 Transformed Polynomials for Nonlinear Autoregressive Models of the Conditional Mean by Francisco Blasques 2012 Composite Valuation of Immaterial Damage in Flooding: Value of Statistical Life, Value of Statistical Evacuation and Value of Statistical Injury by Marija Bockarjova Piet Rietveld Erik T. Verhoef 2012 Scale, Scope and Cognition: Context Analysis of Multiple Stated Choice Experiments on the Values of Life and Limb by Marija Bockarjova Piet Rietveld Erik T. Verhoef 2012 Identification of treatment effects in a triangular system of equations by Sung Jae Jun Joris Pinkse Haiqing Xu Nese Yildiz 2012 Turkiye Icin Bir Reel Iktisadi Faaliyet Gostergesi by S. 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Maheu 2012 Plot and Household-Level Determinants of Sustainable Agricultural Practices in Rural Tanzania by Kassie, Menale Jaleta, Moti Shiferaw, Bekele Mmbando, Frank Muricho, Geoffrey 2012 Optimal Dynamic Contracting by Marco Battaglini Rohit Lamba 2012 One-Sided Uncertainty And Delay In Reputational Bargaining by Dilip Abreu David Pearce Ennio Stacchetti 2012 Games in Preference Form and Preference Rationalizability by Stephen Morris Satoru Takahashi 2012 A non-linear Leontieftype input-output model by Michaelides, Panayotis G. Belegri-Roboli, Athena Markaki, Maria 2012 La brecha del producto y el producto potencial en Venezuela: una estimacin SVAR by Acevedo Rueda, Rafael Alexis Mora Mora, Jos U. Harmath Fernndez, Pedro Alexander 2012 (BVAR) priors by Matkovskyy, Roman 2012 : - by Matkovskyy, Roman 2012 Stylized facts of the daily and monthly returns for the European stock indices during 2007-2012 by Panait, Iulian Constantinescu, Alexandru 2012 Simplifying the estimation of difference in differences treatment effects with Stata by Villa, Juan M. 2012 Exchange rate modelling for Lithuania and Switzerland by Rimgailaite, Ramune 2012 Volatility modelling of foreign exchange rate: discrete GARCH family versus continuous GARCH by Ari, Yakup 2012 Assessing Impact of Health Oriented Aid on Infant Mortality Rates by Yousuf, Ahmed Sadek 2012 Terrorism Its Impact On Foreign Flows: Lessons From Pakistan by Iqbal, Javed Mehmood, Sultan 2012 A New Pseudo-Bayesian Model of Investors Behavior in Financial Crises by Guo, Xu Lam, Kin Wong, Wing-Keung Zhu, Lixing 2012 On the predictive power of implied volatility indexes: A comparative analysis with GARCH forecasted volatility by Bentes, Sonia R Menezes, Rui 2012 The Index of the Financial Safety (IFS) of South Africa and Bayesian Estimates for IFS Vector-Autoregressive Model by Matkovskyy, Roman 2012 The comparison of optimization algorithms on unit root testing with smooth transition by Omay, Tolga 2012 Forecasting 2012 United States Presidential election using Factor Analysis, Logit and Probit Models by Sinha, Pankaj Thomas, Ashley Rose Ranjan, Varun 2012 Stock Market Integration and International Portfolio Diversification between U. 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Paul Lacombe, Donald J. Piras, Gianfranco 2012 Short-run forecasting of the euro-dollar exchange rate with economic fundamentals by Dal Bianco, Marcos Camacho, Maximo Perez Quiros, Gabriel 2012 A new measure of earnings forecast uncertainty by Sheng, Xuguang Thevenot, Maya 2012 Econometric modeling and value-at-risk using the Pearson type-IV distribution by Stavroyiannis, S. Makris, I. Nikolaidis, V. 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