The determinants of the hotel sector revenues: The case of French Polynesia

2019 ◽  
Vol 26 (5) ◽  
pp. 809-829
Author(s):  
Gil Montant
Keyword(s):  
Least Squares ◽  
Generalized Least Squares ◽  
French Polynesia ◽  
Ordinary Least Squares ◽  
Panel Regression ◽  
Geographical Distance ◽  
Explanatory Variables ◽  
Basic Model ◽  
Hotel Sector ◽  
The Impact

This article is an empirical analysis focused on the hotel sector in French Polynesia in 2007–2017. One assesses the impact of a set of variables on the French Polynesian hotel sector monthly revenues through a gravity model. First, one specifies a basic model that embeds several potential explanatory variables (the exchange rate (both nominal and real), the rate of unemployment, the geographical distance, some specific historical events, etc.). Next, a second model is specified so as to assess the impact of hotel capacities measured by the number of bedrooms offered. Estimates rest on an unbalanced monthly panel database that embeds main countries from where tourists present in French Polynesia are originated. In order to compare results, each specification is estimated by two methods: classical panel regression (Ordinary least squares /Generalized least squares) and pseudo Poisson maximum likelihood. Both methods lead to coherent results.

Liberalization, Import of Capital Goods, and Industrial Exports: Evidence from Indian Manufacturing Sectors

2020 ◽  
pp. 239395752097478
Author(s):  
R. Rijesh
Keyword(s):  
Least Squares ◽  
Positive Impact ◽  
Manufacturing Sector ◽  
Generalized Least Squares ◽  
Ordinary Least Squares ◽  
Capital Goods ◽  
Export Prices ◽  
Manufacturing Sectors ◽  
World Demand ◽  
The Impact

This article examines the impact of capital goods import on Indian manufacturing exports at the sectoral level. Import of capital goods provides dynamic productivity gains through quality, variety, and cost-efficiency channels that further boost manufacturing exports. Since trade liberalization facilitates this process, we presumed that better access to capital inputs would enhance Indian exports for 15 major manufacturing sectors at the 3-digit level from 1997 to 2016. The panel regression analysis based on fixed effect(s) feasible generalized least squares (FGLS), and ordinary least squares (OLS) indicate that, after controlling for world demand, relative export prices, and in-house research and development (R&D), the capital goods import has a positive and statistically significant impact on the aggregate manufacturing sector. The OLS estimates at the sectoral level further confirm the positive impact across nine major sectors. In general, the engineering sectors such as metals, machinery and transport equipment, and traditional labor-intensive sectors like textiles show positive benefit from these technology imports.

Estimation of Models with Variable Coefficients

1991 ◽  
Vol 3 ◽  
pp. 27-49 ◽  
Author(s):  
John E. Jackson
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Maximum Likelihood ◽  
Least Squares ◽  
Generalized Least Squares ◽  
Ordinary Least Squares ◽  
Variable Coefficients ◽  
Coefficient Estimates ◽  
Explanatory Variables ◽  
Varying Coefficients

The ordinary least squares (OLS) estimator gives biased coefficient estimates if coefficients are not constant for all cases but vary systematically with the explanatory variables. This article discusses several different ways to estimate models with systematically and randomly varying coefficients using estimated generalized least squares and maximum likelihood procedures. A Monte Carlo simulation of the different methods is presented to illustrate their use and to contrast their results to the biased results obtained with ordinary least squares. Several applications of the methods are discussed and one is presented in detail. The conclusion is that, in situations with variables coefficients, these methods offer relatively easy means for overcoming the problems.

scholarly journals Timely loss recognition in Brazilian firms under corruption investigation

2021 ◽  
Vol 32 (86) ◽  
pp. 224-240
Author(s):  
Silvia Pereira da Rocha ◽  
Francisco Antonio Bezerra
Keyword(s):  
Least Squares ◽  
Accounting Information ◽  
Estimation Method ◽  
Generalized Least Squares ◽  
Ordinary Least Squares ◽  
Business Environment ◽  
Quality Of Accounting Information ◽  
Accounting Reports ◽  
The Impact

ABSTRACT This article evaluates the impact of the disclosure of the participation of Brazilian firms listed on the Bolsa Brasil Balcão (B3) in corruption scandals through media scrutiny and by disclosure of independent auditors on the quality of accounting information, measured from the perspective of accounting conservatism. We examine the possible theoretical link between the disclosure of corruption scandals and the quality of accounting information in the Brazilian context. Brazil has gone through successive corruption scandals involving firms and government entities in different levels. Accounting can be an important tool to mitigate said risks based on the artifacts it has to inform key stakeholders. However, it is necessary to identify the extent to which these artifacts can be influenced by the actors involved in these scandals. The research places accounting as an instrument subject to pressures from different interests and that may be shaped to them. Although accounting is an instrument that must aim to reduce information asymmetry, preventing the harmful effects of corruption, in specific contexts, it can be used in the opposite direction, such as in cases of corruption and economic crises. We used the model based on Ball and Shivakumar (2005) with specific modeling characteristics for corruption and crisis. The models were estimated using the Stata 13 software using the pooled approach using the Ordinary Least Squares (OLS) estimation method, clustered by year and economic sector, and the Generalized Least Squares (GSL) estimator. The results point to the presence of conservatism when disclosing involvement in investigations of corruption crimes in Brazil. This behavior was less intense in firms effectively mentioned in these events. These results highlight the relevance of studies aimed at clarifying the connections between corruption and accounting reports, enabling the development of measures to curb corruption in the business environment.

scholarly journals Initial coin offerings and the cryptocurrency hype - the moderating role of exogenous and endogenous signals

2021 ◽  
Author(s):  
Ferdinand Thies ◽  
Sören Wallbach ◽  
Michael Wessel ◽  
Markus Besler ◽  
Alexander Benlian
Keyword(s):  
Least Squares ◽  
Ordinary Least Squares ◽  
High Quality ◽  
Academic Interest ◽  
Entrepreneurial Ventures ◽  
Asset Class ◽  
The Impact ◽  
Moderating Role ◽  
Initial Coin Offerings

AbstractInitial coin offerings (ICOs) have recently emerged as a new financing instrument for entrepreneurial ventures, spurring economic and academic interest. Nevertheless, the impact of exogenous and endogenous signals on the performance of ICOs as well as the effects of the cryptocurrency hype and subsequent downfall of Bitcoin between 2016 and 2019 remain underexplored. We applied ordinary least squares (OLS) regressions based on a dataset containing 1597 ICOs that covers almost 2.5 years. The results show that exogenous and endogenous signals have a significant effect on the funds raised in ICOs. We also find that the Bitcoin price heavily drives the performance of ICOs. However, this hype effect is moderated, as high-quality ICOs are not pegged to these price developments. Revealing the interplay between hypes and signals in the ICO’s asset class should broaden the discussion of this emerging digital phenomenon.

REDUNDANCY OF MOMENT CONDITIONS AND THE EFFICIENCY OF OLS IN SUR MODELS

2008 ◽  
Vol 24 (5) ◽  
pp. 1456-1460 ◽  
Author(s):  
Hailong Qian
Keyword(s):  
Least Squares ◽  
Asymptotic Efficiency ◽  
Generalized Method Of Moments ◽  
Sufficient Conditions ◽  
Generalized Least Squares ◽  
Ordinary Least Squares ◽  
American Statistical Association ◽  
Orthogonality Condition ◽  
Moment Conditions ◽  
Necessary And Sufficient

In this note, based on the generalized method of moments (GMM) interpretation of the usual ordinary least squares (OLS) and feasible generalized least squares (FGLS) estimators of seemingly unrelated regressions (SUR) models, we show that the OLS estimator is asymptotically as efficient as the FGLS estimator if and only if the cross-equation orthogonality condition is redundant given the within-equation orthogonality condition. Using the condition for redundancy of moment conditions of Breusch, Qian, Schmidt, and Wyhowski (1999, Journal of Econometrics 99, 89–111), we then derive the necessary and sufficient condition for the equal asymptotic efficiency of the OLS and FGLS estimators of SUR models. We also provide several useful sufficient conditions for the equal asymptotic efficiency of OLS and FGLS estimators that can be interpreted as various mixings of the two famous sufficient conditions of Zellner (1962, Journal of the American Statistical Association 57, 348–368).

scholarly journals The effect of creative corporate culture and intangibility on the performance of foreign firms traded on the NYSE

2018 ◽  
Vol 15 (4) ◽  
pp. 356-372 ◽  
Author(s):  
Marcia Martins Mendes De Luca ◽  
Paulo Henrique Nobre Parente ◽  
Emanoel Mamede Sousa Silva ◽  
Ravena Rodrigues Sousa
Keyword(s):  
New York ◽  
Least Squares ◽  
Corporate Culture ◽  
Corporate Performance ◽  
Stock Exchange ◽  
Generalized Least Squares ◽  
Ordinary Least Squares ◽  
Foreign Firms ◽  
Content Type ◽  
Negative Effect

Purpose Following the tenets of resource-based view, the present study aims to investigate the effect of creative corporate culture according to the competing values framework model at the level of corporate intangibility and its respective repercussions on performance. Design/methodology/approach The sample included 117 non-USA foreign firms traded on the New York Stock Exchange (NYSE), which issued annual financial reports between 2009 and 2014 using the 20-F form. To meet the study objectives, in addition to the descriptive and comparative analyses, the authors performed regression analyses with panel data, estimating generalized least-squares, two-stage least-squares and ordinary least-squares. Findings Creative culture had a negative effect on the level of intangibility and corporate performance, while the level of intangibility did not appear to influence corporate performance. When combined, creative culture and intangibility had a potentially negative effect on corporate results. In conclusion, creative corporate culture had a negative effect on performance, even in firms with higher levels of intangibility, characterized by elements like experimentation and innovation. Originality/value Although the study hypotheses were eventually rejected, the analyses are relevant to both the academic setting and the market because of the organizational and institutional aspects evaluated, especially in relation to intangibility and creative culture and in view of the unique cross-cultural approach adopted. Within the corporate setting, the study provides a spectrum of stakeholders with tools to identify the profile of foreign firms traded on the NYSE.

scholarly journals The Impact of Industrialization, Trade Openness, Financial Development, and Energy Consumption on Economic Growth in Indonesia

Economies ◽  
2021 ◽  
Vol 9 (4) ◽  
pp. 174
Author(s):  
Khalid Eltayeb Elfaki ◽  
Rossanto Dwi Handoyo ◽  
Kabiru Hannafi Ibrahim
Keyword(s):  
Economic Growth ◽  
Energy Consumption ◽  
Least Squares ◽  
Financial Development ◽  
Correction Term ◽  
Trade Openness ◽  
Ordinary Least Squares ◽  
Distributed Lag ◽  
Long Run ◽  
The Impact

This study aimed to scrutinize the impact of financial development, energy consumption, industrialization, and trade openness on economic growth in Indonesia over the period 1984–2018. To do so, the study employed the autoregressive distributed lag (ARDL) model to estimate the long-run and short-run nexus among the variables. Furthermore, fully modified ordinary least squares (FMOLS), dynamic least squares (DOLS), and canonical cointegrating regression (CCR) were used for a more robust examination of the empirical findings. The result of cointegration confirms the presence of cointegration among the variables. Findings from the ARDL indicate that industrialization, energy consumption, and financial development (measured by domestic credit) positively influence economic growth in the long run. However, financial development (measured by money supply) and trade openness demonstrate a negative effect on economic growth. The positive nexus among industrialization, financial development, energy consumption, and economic growth explains that these variables were stimulating growth in Indonesia. The error correction term indicates a 68% annual adjustment from any deviation in the previous period’s long-run equilibrium economic growth. These findings provide a strong testimony that industrialization and financial development are key to sustained long-run economic growth in Indonesia.

scholarly journals Determinants of Credit Risk in the Banking Sector of Ghana: A Panel Co-integration Approach

2020 ◽  
Vol 5 (4) ◽  
Author(s):  
Thomas Appiah ◽  
Frank Bisiw
Keyword(s):  
Credit Risk ◽  
Least Squares ◽  
Banking Sector ◽  
Ordinary Least Squares ◽  
Capital Adequacy ◽  
High Rate ◽  
Long Run ◽  
Integration Techniques ◽  
The Government ◽  
The Impact

The economic development of any nation hinges on the health of its financial system. In recent years, the health of the Ghanaian Banking sector has been affected severely as a result of high levels of non-performing loans (NPLs), which has been identified as a major threat to the overall profitability and survival of banks. To minimize the impact of NPLs on the financial sector, key stakeholders such as the government, bank officials and regulators are working hard in that regard. However, any policy response aimed at dealing with the high rate of non-performing loans first requires the understanding of the underlying determinants of NPLs. Against this backdrop, this paper apply panel co-integration techniques to investigate the determinants of credit risk (NPLs) in the banking sector of Ghana.  We use NPL as a proxy to measure credit risk and assess how it is influenced by macroeconomic and bank-specific factors. A balanced panel data of 16 universal banks in Ghana from 2010 to 2016 has been analyzed using Panel co-integration techniques such as Fully Modified Ordinary Least Squares (FMOLS) and Dynamic Ordinary Least Squares (DOLS). Our result shows that growth in the economy, measured by Gross Domestic Product (GDP) has significant influence on the NPLs of banks in the long-run. The results further revealed that capital adequacy, profitability and liquidity of banks are significant predictors of NPLs. However, our results suggest that bank size, inflation and interest rate have statistically insignificant influence on the NPLs of Ghanaian banks. The study recommend, among others, that whereas it is important for government and policymakers to work to improve macroeconomic outcomes, banks should also improve their capital adequacy, profitability, and efficiency position as these bank-specific interventions could significantly improve credit quality and minimize NPLs.

Nuisance vs. Substance: Specifying and Estimating Time-Series-Cross-Section Models

1996 ◽  
Vol 6 ◽  
pp. 1-36 ◽  
Author(s):  
Nathaniel Beck ◽  
Jonathan N. Katz
Keyword(s):  
Time Series ◽  
Least Squares ◽  
Cross Section ◽  
Generalized Least Squares ◽  
Ordinary Least Squares ◽  
Correlated Errors ◽  
Section Data ◽  
Variable Approach ◽  
Parameter Heterogeneity ◽  
Lagged Dependent Variable

In a previous article we showed that ordinary least squares with panel corrected standard errors is superior to the Parks generalized least squares approach to the estimation of time-series-cross-section models. In this article we compare our proposed method with another leading technique, Kmenta's “cross-sectionally heteroskedastic and timewise autocorrelated” model. This estimator uses generalized least squares to correct for both panel heteroskedasticity and temporally correlated errors. We argue that it is best to model dynamics via a lagged dependent variable rather than via serially correlated errors. The lagged dependent variable approach makes it easier for researchers to examine dynamics and allows for natural generalizations in a manner that the serially correlated errors approach does not. We also show that the generalized least squares correction for panel heteroskedasticity is, in general, no improvement over ordinary least squares and is, in the presence of parameter heterogeneity, inferior to it. In the conclusion we present a unified method for analyzing time-series-cross-section data.

The impact of gender inequality in education and employment on economic performance in Turkey: evidence from a cointegration approach

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ömer Esen ◽  
Gamze Yıldız Seren
Keyword(s):  
Least Squares ◽  
Economic Performance ◽  
Ordinary Least Squares ◽  
Estimation Methods ◽  
Content Type ◽  
Cointegration Tests ◽  
Johansen Cointegration ◽  
Education And Employment ◽  
The Impact

PurposeThis study aims to empirically examine the impact of gender-based inequalities in both education and employment on economic performance using the dataset of Turkey for the period 1975–2018.Design/methodology/approachThis study employs Johansen cointegration tests to analyze the existence of a long-term relation among variables. Furthermore, dynamic ordinary least squares (DOLS) and fully modified ordinary least squares (FMOLS) estimation methods are performed to determine the long-run coefficients.FindingsThe findings from the Johansen cointegration analysis confirm that there is a long-term cointegration relation between variables. Moreover, DOLS and FMOLS results reveal that improvements in gender equality in both education and employment have a strong and significant impact on real gross domestic product (GDP) per capita in the long term.Originality/valueThe authors expect that this study will make remarkable contributions to the future academic studies and policy implementation, as it examines the relation among the variables by including the school life expectancy from primary to tertiary based on the gender parity index (GPI), the gross enrollment ratio from primary to tertiary based on GPI and the ratio of female to male labor force participation (FMLFP) rate.

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