Effects of Initial Conditions on Monte Carlo Estimates of Bias in Estimating Functional Relationships

1988 ◽  
Vol 45 (1) ◽  
pp. 185-187 ◽  
Author(s):  
Robert G. Kope
Keyword(s):  
Monte Carlo ◽  
Time Series Data ◽  
Initial Conditions ◽  
Series Data ◽  
Stock Size ◽  
Functional Relationships ◽  
Stock Recruitment ◽  
Relationship Of ◽  
Parameter Values ◽  
The Relationship

Some of the results presented by Walters (1985. Can. J. Fish. Aquat. Sci. 42: 147–149) for the magnitude of bias in estimating functional relationships from time series data resulted from his choice of initial stock size in Monte Carlo simulations rather than the dynamics of the model. Walters used the same initial stock size in each simulation while varying parameters in the stock–recruitment relationship. Starting each simulation at the equilibrium stock size or allowing initial stock size to vary randomly produces larger estimates of bias and leads to different conclusions about the relationship of bias to parameter values in the model.

Bias in the Estimation of Functional Relationships from Time Series Data

1985 ◽  
Vol 42 (1) ◽  
pp. 147-149 ◽  
Author(s):  
Carl J. Walters
Keyword(s):  
Time Series ◽  
Measurement Errors ◽  
Time Series Data ◽  
Series Data ◽  
Parameter Estimates ◽  
Natural Experiments ◽  
Independent Variables ◽  
Functional Relationships ◽  
Stock Recruitment ◽  
The Relationship

Functional relationships, such as stock–recruitment curves, are generally estimated from time series data where natural "random" factors have generated both deviations from the relationship and also informative variation in the independent variables. Even in the absence of measurement errors, such natural experiments can lead to severely biased parameter estimates. For stock–recruitment models, the bias is misleading for management: the stock will appear too productive when it is low, and too unproductive when it is large. The likely magnitude of such biases can and should be determined for any particular case by Monte Carlo simulations.

Influence of systemic banking crisis and currency crisis on the relationship of export and economic growth

2017 ◽  
Vol 10 (1) ◽  
pp. 82-110
Author(s):  
Syed Ali Raza ◽  
Mohd Zaini Abd Karim
Keyword(s):  
Economic Growth ◽  
Time Series ◽  
Financial Crises ◽  
Currency Crises ◽  
Time Series Data ◽  
Banking Crises ◽  
Series Data ◽  
Content Type ◽  
Relationship Of ◽  
The Relationship

Purpose This study aims to investigate the influence of systemic banking crises, currency crises and global financial crisis on the relationship between export and economic growth in China by using the annual time series data from the period of 1972 to 2014. Design/methodology/approach The Johansen and Jeuuselius’ cointegration, auto regressive distributed lag bound testing cointegration, Gregory and Hansen’s cointegration and pooled ordinary least square techniques with error correction model have been used. Findings Results indicate the positive and significant effect of export of goods and services on economic growth in both long and short run, whereas the negative influence of systemic banking crises and currency crises over economic growth is observed. It is also concluded that the impact of export of goods and service on economic growth becomes insignificant in the presence of systemic banking crises and currency crises. The currency crises effect the influence of export on economic growth to a higher extent compared to systemic banking crises. Surprisingly, the export in the period of global financial crises has a positive and significant influence over economic growth in China, which conclude that the global financial crises did not drastically affect the export-growth nexus. Originality/value This paper makes a unique contribution to the literature with reference to China, being a pioneering attempt to investigate the effects of systemic banking crises and currency crises on the relationship of export and economic growth by using long-time series data and applying more rigorous econometric techniques.

scholarly journals The Effect of Foreign Direct Investment on Indonesia’s Economic Growth

2016 ◽  
Vol 1 (2) ◽  
pp. 18-24
Author(s):  
Abdul Hadi Ilman
Keyword(s):  
Economic Growth ◽  
Foreign Direct Investment ◽  
Direct Investment ◽  
Time Series Data ◽  
Series Data ◽  
Linear Regression Method ◽  
Domestic Investment ◽  
Relationship Of ◽  
The Impact ◽  
The Relationship

The relationship of Foreign Direct Investment (FDI) on economic growth is one of the most debatable topic in economic. This study is aiming to investigate the impact of FDI on economic growth in Indonesia. This research using linear regression method which base on time series data from 1981 to 2012. A Major finding is there is no special relationship between FDI and economic growth, both directly and indirectly. Moreover, FDI does crowd-in the domestic investment and is no significance evidence to prove that FDI is more efficient on economic growth than domestic investment.

ANALISIS HUBUNGAN ANTARA HARGA MINYAK, PASAR SAHAM, DAN NILAI TUKAR DI INDONESIA

2019 ◽  
Vol 1 (4) ◽  
Author(s):  
Nadia Kurnianti ◽  
Idris Idris
Keyword(s):  
Time Series ◽  
Exchange Rates ◽  
Stock Markets ◽  
Time Series Data ◽  
Oil Prices ◽  
Series Data ◽  
Var Model ◽  
Causality Relationship ◽  
Relationship Of ◽  
The Relationship

The aim of this research is to analyze the relationship of causality between oil prices, stocks market, and exchange rates in Indonesia using VAR model. The data used in this study is time series data from January 2014 until December 2018 that was obtained from the relevant institutions. The variables use are oil prices (X1), stocks market (X2), and exchange rates (X3). The method used in this study is Vector Auto Reggression (VAR). The finding has shown that there are no causality relationship between the oil prices, stock markets, and exchanger rates. The finding also shown that there is only directional relationship between exchange rates with stocks market.

scholarly journals Impact of Public & Foreign Direct Investment on the Economy of Bangladesh

2021 ◽  
pp. 227-246
Author(s):  
Md Kamrul Islam ◽  
Sabid Khan ◽  
Zareen Haider
Keyword(s):  
Growth Rate ◽  
Time Series Data ◽  
Public Investment ◽  
Negative Relationship ◽  
Series Data ◽  
Fdi Inflows ◽  
Fixed Capital Formation ◽  
Relationship Of ◽  
The Impact ◽  
The Relationship

This paper is to investigate the impact of public investment and FDI on GDP growth of Bangladesh. The Gross Fixed Capital Formation represents public investment of our country and we have taken FDI (inflows) as the variable while the GDP is the dependent variable. The time series data has been included here, which will be kept stationary, followed by a regression. As public investment and FDI are the independent variables, it is expected that they both have a positive relation with the dependent variable. Although, FDI may have a negative relationship to the growth. The relationship of FDI with growth rate can be used to show whether a country is in scarce of capital or not. The objective is to identify the relationship of public investment and FDI to the growth and to what extent these investments have an impact on the growth rate. By showing the estimated relationship of FDI to the GDP or growth, we are going to know whether our country is capital abundant or labor abundant.

Physiological time-series analysis: what does regularity quantify?

1994 ◽  
Vol 266 (4) ◽  
pp. H1643-H1656 ◽  
Author(s):  
S. M. Pincus ◽  
A. L. Goldberger
Keyword(s):  
Time Series ◽  
Time Series Data ◽  
Approximate Entropy ◽  
Series Data ◽  
Data Sets ◽  
Heart Rate Data ◽  
Mathematical Properties ◽  
Relationship Of ◽  
Algorithm Implementation ◽  
The Relationship

Approximate entropy (ApEn) is a recently developed statistic quantifying regularity and complexity that appears to have potential application to a wide variety of physiological and clinical time-series data. The focus here is to provide a better understanding of ApEn to facilitate its proper utilization, application, and interpretation. After giving the formal mathematical description of ApEn, we provide a multistep description of the algorithm as applied to two contrasting clinical heart rate data sets. We discuss algorithm implementation and interpretation and introduce a general mathematical hypothesis of the dynamics of a wide class of diseases, indicating the utility of ApEn to test this hypothesis. We indicate the relationship of ApEn to variability measures, the Fourier spectrum, and algorithms motivated by study of chaotic dynamics. We discuss further mathematical properties of ApEn, including the choice of input parameters, statistical issues, and modeling considerations, and we conclude with a section on caveats to ensure correct ApEn utilization.

scholarly journals Relationship between Remittance and Economic Growth: Evidence from Bangladesh

2018 ◽  
Vol 5 (3) ◽  
pp. 93-98
Author(s):  
Md. Sujahangir Kabir Sarkar ◽  
Md. Zillur Rahman ◽  
Mohammad Muzahidul Islam ◽  
Md. Mehedi Hasan Sikdar ◽  
Abul Basher Khan
Keyword(s):  
Economic Growth ◽  
Time Series Data ◽  
Capital Formation ◽  
Series Data ◽  
Domestic Saving ◽  
Consumption Expenditure ◽  
Average Growth ◽  
Final Consumption ◽  
Relationship Of ◽  
The Relationship

Remittance is one of the major sources of capital especially for the developing countries like Bangladesh. This study attempts to explore the relationship between remittance and economic growth in Bangladesh. Time series data from 1995-2016 extracted from the World Bank database as well as Bangladesh Bank statistics were used to measure the relationship of remittance and gross domestic product (GDP) with some other variables such as gross capital formation, gross domestic saving and household final consumption expenditure. Pearson’s correlation coefficient is estimated between the variables. Moreover, annual growth (%) of remittance earning by Bangladesh has been calculated and compared with the GDP growth of Bangladesh. The study has found that on an average, remittance of Bangladesh has been increased by 10.85% from 1995-2016 which is higher than the average growth of the country’s GDP. It has revealed that there is a positive relationship of remittance with the GDP, gross capital formation, domestic saving and household final consumption expenditure in case of Bangladesh. However, there is a frequent fluctuation of remittance flow in Bangladesh in the recent years. Thus, this study recommends that Bangladesh should take proper initiatives for maintaining an increasing trend of remittance in the coming years which would be useful for the socio-economic development of the country.  

Testing Structural Break in the Relationship Between Exchange Rate and Macroeconomic Variables

2019 ◽  
Vol 23 (4) ◽  
pp. 442-453 ◽  
Author(s):  
Saidia Jeelani ◽  
Joity Tomar ◽  
Tapas Das ◽  
Seshanwita Das
Keyword(s):  
Exchange Rate ◽  
Structural Breaks ◽  
Time Series Data ◽  
Structural Break ◽  
Series Data ◽  
Ripple Effect ◽  
Macroeconomic Factors ◽  
Parameter Instability ◽  
Macroeconomic Variables ◽  
The Relationship

The article aims to study the relationship between those macroeconomic factors that the affect (INR/USD) exchange rate (ER). Time series data of 40 years on ER, GDP, inflation, interest rate (IR), FDI, money supply, trade balance (TB) and terms of trade (ToT) have been collected from the RBI website. The considered model has suggested that only inflation, TB and ToT have influenced the ER significantly during the study period. Other macroeconomic variables such as GDP, FDI and IR have not significantly influenced the ER during the study period. The model is robust and does not suffer from residual heteroscedasticity, autocorrelation and non-normality. Sometimes the relationship between ER and macroeconomic variables gets affected by major economic events. For example, the Southeast Asian crisis caused by currency depreciation in 1997 and sub-prime loan crisis of 2008 severely strained the national economies. Any global economic turmoil will affect different economic variables through ripple effect and this, in turn, will affect the ER of different economies differently. The article has also diagnosed whether there is any structural break or not in the model by applying Chow’s Breakpoint Test and have obtained multiple breaks between 2003 and 2009. The existence of structural breaks during 2003–2009 is explained by the fact that volume of crude oil imported by India is high and oil price rise led to a deficit in the TB alarmingly, which caused a structural break or parameter instability.

scholarly journals Non-bank financial institutions and economic growth: Evidence from Africa’s three largest economies

2017 ◽  
Vol 20 (1) ◽  
Author(s):  
Ronald Rateiwa ◽  
Meshach J. Aziakpono
Keyword(s):  
Economic Growth ◽  
South Africa ◽  
Financial Institutions ◽  
Time Series Data ◽  
Bank Lending ◽  
Series Data ◽  
The Sustainable Development ◽  
Long Run ◽  
The Relationship

Background: In order for the post-2015 world development agenda – termed the sustainable development goals (SDGs) – to succeed, there is a pronounced need to ensure that available resources are used more effectively and additional financing is accessed from the private sector. Given that traditional bank lending has slowed down, the development of non-bank financing has become imperative. To this end, this article intends to empirically test the role of non-bank financial institutions (NBFIs) in stimulating economic growth.Aim: The aim of this article is to empirically test the existence of a long-run equilibrium relationship between economic growth and the development of NBFIs, and the causality thereof.Setting: The empirical assessment uses time-series data from Africa’s three largest economies, namely, Egypt, Nigeria and South Africa, over the period 1971–2013.Methods: This article uses the Johansen cointegration and vector error correction model within a country-specific setting.Results: The results showed that the long-run relationship between NBFI development and economic growth is relatively stronger in Egypt and South Africa, than in Nigeria. Evidence in respect of Nigeria shows that such a relationship is weak. The nature of the relationship between NBFI development and economic growth in Egypt is positive and significant, and predominantly bidirectional. This suggests that a virtuous relationship between NBFIs and economic growth exists in Egypt. In South Africa, the relationship is positive and significant and predominantly runs from NBFI development to economic growth, implying a supply-leading phenomenon. In Nigeria, the results are weak and mixed.Conclusion: The study concludes that in countries with more developed financial systems, the role of NBFIs and their importance to the economic growth process are more pronounced. Thus, there is need for developing policies targeted at developing the NBFI sector, given their potential to contribute to economic growth.

scholarly journals Retrospectives: The Introduction of the Cobb–Douglas Regression

2012 ◽  
Vol 26 (2) ◽  
pp. 223-236 ◽  
Author(s):  
Jeff Biddle
Keyword(s):  
Time Series Data ◽  
Series Data ◽  
Mathematical Representation ◽  
Least Squares Regression ◽  
Empirical Measures ◽  
Stable Relationship ◽  
Initial Application ◽  
Economic Association ◽  
The Relationship ◽  
Theory Of Production

At the 1927 meetings of the American Economic Association, Paul Douglas presented a paper entitled “A Theory of Production,” which he had coauthored with Charles Cobb. The paper proposed the now familiar Cobb–Douglas function as a mathematical representation of the relationship between capital, labor, and output. The paper's innovation, however, was not the function itself, which had originally been proposed by Knut Wicksell, but the use of the function as the basis of a statistical procedure for estimating the relationship between inputs and output. The paper's least squares regression of the log of the output-to-capital ratio in manufacturing on the log of the labor-to-capital ratio—the first Cobb–Douglas regression—was a realization of Douglas's innovative vision that a stable relationship between empirical measures of inputs and outputs could be discovered through statistical analysis, and that this stable relationship could cast light on important questions of economic theory and policy. This essay provides an account of the introduction of the Cobb–Douglas regression: its roots in Douglas's own work and in trends in economics in the 1920s, its initial application to time series data in the 1927 paper and Douglas's 1934 book The Theory of Wages, and the early reactions of economists to this new empirical tool.

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