Think tanks, rankings, the Brookings Institution, and the rise of non-Western think tanks

This study entitled Analysis of Factors Affecting Demand Beef In The purpose of this study is going to analyze the effect of the price of beef, chicken meat prices, the gross regional domestic product (GRDP), and the total population of the demand for beef in the city of Surabaya. The types and sources of data used quantitative approach with secondary data time series observations in the period 2004-2013. The research variables consist of the dependent variable or dependent that demand for beef (QDS). Independent variables or smoking that is the price of beef (Pds), the price of chicken meat (Pda), regional gross domestic product (Y) and population (P). Data analysis tools using multiple linear regression method. Based on the results of multiple linear regression analysis of the results obtained: QDS = 1.304E7 - Pds 396 581 - 237 988 Pda + 2.345E-7 Y + 4272 P + e. Retrieved tcount beef prices amounted to 1.159, 0.263 for chicken meat prices, the gross domestic product (GDP) of 0.731 and a population of 0.119. As for the simultaneous testing of F values obtained (2.009) <F table (5.192). Thus H0 and H1 rejected. The conclusion of this study indicate that the price of beef, chicken meat prices, the gross domestic product (GDP) and population affect the demand for beef in the city of Surabaya. Keywords: Price of Beef, Chicken Meat prices, the GDP and Population

The purpose of this research is to obtain empirical evidence of the influence of the inflation rate, interest rates on Bank Indonesia Certificates (SBI) and Gross Domestic Product (GDP). The independent variables used are inflation, SBI interest rates, and Gross Domestic Product (GDP). The dependent variable used is the Composite Stock Price Index (IHSG) policy. In this study, the macroeconomic factors used were the inflation rate, SBI interest rates and GDP. The data taken is the monthly closing price of each dependent and independent variable. The sampling method is 60 months of closing price data. The data used is secondary data with documentation data collection methods. The analytical tool used is multiple linear regression. The partial results of the study show that only GDP has a significant effect on the JCI on the IDX, while the inflation rate and SBI interest rates do not have a significant effect on the IHSG on the IDX. And simultaneously shows that the inflation rate, SBI interest rates and GDP have a significant effect on the IHSG on the IDX. Keywords: JCI, inflation rate, SBI interest rate, GDP. The purpose of this research is to obtain empirical evidence of the influence of the inflation rate, interest rates on Bank Indonesia Certificates (SBI) and Gross Domestic Product (GDP). The independent variables used are inflation, SBI interest rates, and Gross Domestic Product (GDP). The dependent variable used is the Composite Stock Price Index (IHSG) policy. In this study, the macroeconomic factors used were the inflation rate, SBI interest rates and GDP. The data taken is the monthly closing price of each dependent and independent variable. The sampling method is 60 months of closing price data. The data used is secondary data with documentation data collection methods. The analytical tool used is multiple linear regression. The partial results of the study show that only GDP has a significant effect on the JCI on the IDX, while the inflation rate and SBI interest rates do not have a significant effect on the IHSG on the IDX. And simultaneously shows that the inflation rate, SBI interest rates and GDP have a significant effect on the IHSG on the IDX. Keywords: JCI, inflation rate, SBI interest rate, GDP.

This study aims to determine the effect of exports, imports and population on the Gross Domestic Product (GDP) of case studies in Indonesia, Malaysia, Singapore, Brunei Darussalam and the Philippines in 2000-2019. This type of research uses quantitative descriptive methods with panel data regression analysis, as well as data collection with documentation techniques, namely the data obtained from word bank data. The results show that exports have a positive and significant effect on gross domestic product with the regression coefficient value on the export variable amounting to 0.589385, which means that every 1% increase in exports will increase GDP by 58.94%, imports have positive and no significant effect on products. Gross domestic product with a regression coefficient value on the import variable is 0.0283 which means that every 1% increase in imports will increase GDP by 2.83%, the population has a positive and significant effect on gross domestic product with the regression coefficient value on the population variable is 14,653 which This means that if there is an increase in the population of 1%, it will increase the gross domestic product by 14.65%, then simultaneously exports, imports and the population will positively and significantly increase the Gross Domestic Product (GDP) with a coefficient value of 0.9693 which means that meaning that the variables of exports, imports and population are able to explain the variable gross domestic product (GDP) of 96.90% while the remaining 3.10% is explained by other variables not mentioned in this study.

This study seeks to examine the impact of financial deepening on economic growth in Nigeria. An annual data covering the period of 1990 – 2017 was used . In other to test the objective of the study, multiple regression techniques were used, also, error correction model was conducted to test the long run equilibrium of the model. Findings revealed that the variable has a long run effect on economic growth since the ECM result reveals a negative and significant relationship. Also based on the short run test, the result reveals that there is a negative and insignificant relationship between the ratio of credit to private sector to gross domestic product (CPS_GDP) and gross domestic product (GDP). T here is also a negative and insignificant relationship between inflation rate (INFL) and gross domestic product (GDP). Furthermore, the result shows that there is a positive and insignificant relationship between the ratio of gross fixed capital formation to gross domestic product and gross domestic product (GDP). Also, it was found that there is a negative and insignificant relationship between the ratio of money supply to gross domestic product in the economy and gross domestic product (GDP). Based on the findings, we recommended that government policy should motive financial institutions to grant low cost loans and advances to private investors and to monitor the use of the loan in the economy. Government should also ensure that they create enabling environment for domestic investors to invest funds. Finally, the government yearly budgets should be directed towards capital expenditure rather than recurrent expenditure in the country

This study aims to determine what affect GDP (Gross Domestic Product) in constant Indonesian prices. The dependent variable used is GDP (Gross Domestic Product), and the independent variables are Islamic stocks, Islamic mutual funds, Islamic bonds (Sukuk), and the BI rate. The data used in this study are monthly during the period 2016: 1-2018: 12 sourced from OJK, BI, and Ministry of Home Affairs. The estimation tool used in this study is the Vector Error Correction Model (VECM) using E-views 7.0. Estimation results show that in the short term, the GDP variable (Gross Domestic Product) itself, Islamic stocks, BI rate, and Islamic mutual funds significantly affect GDP (Gross Domestic Product). In the long run, the estimation results show that sharia stock variables and sharia mutual funds have a significant effect on GDP (Gross Domestic Product). While the sharia bond variable (Sukuk) and the BI rate do not significantly affect GDP (Gross Domestic Product). VECM estimation results in this study also produce important Says, namely IRF (Impulse Response Function) and VDC (Variance Decomposition).

If you want to harvest in the autumn, you need to sow in spring. This ancient wisdom holds true not only for agriculture, but for all economic activities. When nations turned their focus from agriculture to industry, the definition of ‘sowing’ and ‘harvesting’ changed. The latter is relatively easy to identify: it is the nation's wealth in terms of economic growth, employment level, per capita income, exports, and so on. Such achievements point the way not only to re‐election of the politicians who ensure a rich harvest, but also to the well‐being of all its citizens. Slightly harder to define is the ‘sowing’ part—the public and private investments that guarantee economic growth and high employment in the long term. After the industrial revolution took place, governments needed simply to ensure that the social, political and financial structures were in place to encourage entrepreneurs to start businesses and create new jobs in the emerging industrial sector. Now, at a time of globalization, international corporations move to where they can find the best opportunities in terms of employee salaries and governmental incentives. It follows that robust manufacturing processes are being transferred from their traditional locations in the developed world to areas that offer the best financial projections and the lowest cost structures. As a result, the so‐called advanced economies have to find new ways to maintain their privileged status. The common solution is to focus on new discoveries that bring with them ownership of commercially valuable intellectual property and require a phase of development and manufacturing in a highly skilled environment. Thus, the seeds that need to be sown are now investments, from both industry and government, into science and technology, with the aim of creating well‐paid jobs in the high‐tech sector and new products for an increasingly demanding global market. > It …

The study examined the effects of exports to Gross Domestic Product (GDP), employment, and production loans granted in the GDP agriculture of the Philippines. This paper employed descriptive and quantitative techniques to analyze the behavior of GDP, production loans granted (PLG), exports to GDP (EGDP), and employment (EMP) from 2005 to 2015 totalling 33 observations of agriculture, forestry, and fishery sectors. Specifically, panel data analysis was used to assess the effects of APLG, EMP, GDPt-1 and AEGDPt-1 in GDP. The fixed effect model corrected from autocorrelation and heteroscedasticity, a one percentage unit increase in the exports to GDP, on the average, leads to Php 774.96 increase in the GDP, other things equal; and a one-unit increase in employment, on the average, leads to PhP23.55 increase in the GDP, other things equal; a one peso increase in the production loans granted lagged by one period, on the average, leads to Php 0.4760 increase in the GDP, other things equal. Using the fixed effect model, all the explanatory variables such as, exports to GDP, employment and production loans granted lagged by one period exhibited significant effect on the GDP agriculture. Hence, the model is considered satisfactory from statistical perspective. The results from the fixed effect model were consistent with the priori expectations that exports to GDP, employment and production loans granted lagged by one period positively affect the GDP agriculture.

The purpose of this study was to obtain empirical evidence about the effect of leverage, inflation and Gross Domestic Product (GDP) of the share price at PT. Astra Autopart, Tbk. companies in Indonesia Stock Exchange in 2011-2015. The sampling technique in this study using a purposive sampling. With the technique of purposive sampling, all the members of the research samples by criteria. Samples that meet the criteria are used research data. Then followed the classic assumption test and test hypotheses by linear regression. The results of this study demonstrate the regression results in regression equation that Y = 2605,424 + 1561,550 X1 + 2,338 X2 + 38,994X3. T test results showed that the leverage anda GDP (Gross Domestic Product) is positive and significant effect on stock prices, while inflation is not positive and significant effect on stock prices. F test results showed that jointly leverage variables, inflation and GDP variables affecting the stock price significantly. The test results R2 (coefficient of determination) found that the variable leverage, inflation and GDP able to explain 35,4% of the stock price variable, while the remaining 64,6% is explained by other variables.Keywords: leverage, inflation, GDP, and the share priceThe purpose of this study was to obtain empirical evidence about the effect of leverage, inflation and Gross Domestic Product (GDP) of the share price at PT. Astra Autopart, Tbk. companies in Indonesia Stock Exchange in 2011-2015.The sampling technique in this study using a purposive sampling. With the technique of purposive sampling, all the members of the research samples by criteria. Samples that meet the criteria are used research data. Then followed the classic assumption test and test hypotheses by linear regression.The results of this study demonstrate the regression results in regression equation that Y = 2605,424 + 1561,550 X1 + 2,338 X2 + 38,994X3. T test results showed that the leverage anda GDP (Gross Domestic Product) is positive and significant effect on stock prices, while inflation is not positive and significant effect on stock prices. F test results showed that jointly leverage variables, inflation and GDP variables affecting the stock price significantly. The test results R2 (coefficient of determination) found that the variable leverage, inflation and GDP able to explain 35,4% of the stock price variable, while the remaining 64,6% is explained by other variables.Keywords: leverage, inflation, GDP, and the share price

This article discusses an emerging policy and research agenda; systemati- cally linking quality schools with quality cities. There is an historic discon- nect between cities and public education. To dismantle this disconnect, the Center for Cities &amp; Schools was established in 2004, by the Institute of Urban and Regional Development (IURD) at the University of California, Berkeley. The Center holds that high-quality education is a critical compo- nent of broader city and metropolitan policy-making and that invigorating public education and revitalizing neighborhoods are goals that can, and should, be accomplished in tandem. To contextualize the issues and the role of the Center, this paper provides a transcript and discussion of the two keynote addresses at the Center’s fall 2004 symposium, which featured Bruce Katz, a Vice President at the Brookings Institution and founding Director of the Brookings Metropolitan Policy Program, and Dr. Arlene Ackerman, Superintendent of the San Francisco Unified School District.

Small and medium enterprises play a key role in the economic development of many countries. Precisely for that reason, there is research that examines and analyzes this connection and these effects. Numerous studies on the role and importance of small and medium-sized companies, both in BiH and beyond, highlight and point to the importance and need to strengthen the role of small and medium-sized enterprises. Thus, the authors point out that small and medium enterprises are the drivers of development in most countries, while in BiH there is an entrepreneurial initiative but without significant government policy when it comes to implementing business ideas of entrepreneurs and potential entrepreneurs, despite their success spreading to society.Small and medium enterprises are the subject of numerous researches and analyzes. Among these analyzes, it is often examined how small and medium-sized enterprises (SMEs) affect economic growth expressed in gross domestic product (GDP). Research generally confirms that SMEs boost economic growth and development, reduce unemployment, and contribute to innovation. In this context, the aim of this paper is to examine the relationship between individual microeconomic and macroeconomic components related to small and medium enterprises but also to gross domestic product. In this case, the gross domestic product is observed through GDP per capita, and the research examines the effects of the observed variables on GDP per capita. The period covered by the analysis is from 2004 to 2019. Data are on an annual basis. Theoretical and empirical research seeks to answer the following research question: Which components of SME business increase GDP per capita in BiH? The answer to this research question has been investigated using several scientific methods. The research includes a review of the literature, analyzing the data that examine these relations and which indicate their impact on economic growth and development. Examination of the correlation and influence of the analyzed variables was performed using the method of correlation and regression. The obtained research results show that the only factor that has a positive and statistically significant impact on the GDP per capita growth rate has loans granted to the private sector. Other factors, whether positive or negative, do not have a statistically significant impact on GDP per capita. The number of days required for business registration has a negative effect on GDP growth per capita. As the number of days to register a business decreases, so does GDP per capita. On the other hand, insolvency resolution of companies is positively maintained at GDP per capita. The unemployment rate has a negative effect on GDP per capita, while inflation has a positive one. Investments in RiD also have a positive effect on GDP per capita. Such findings indicate that BiH should focus on these factors if it wants to stimulate growth measured through GDP per capita through small and medium enterprises.

We Are What We Measure

Background: The Gross Domestic Product (GDP) emerged as a convenient measure of national economic activity during the Great Depression. It was subsequently adopted by international development economists to track developing countries’ progress so that, despite its severe deficiencies, it became ‘locked in’ by habit, convenience, and policy makers’ preferences. Purpose: This article conceives of GDP as a social intervention fit for evaluation. It shows that the GDP has had a pervasive and pernicious influence on policy making. Since past strategies aimed at dethroning the GDP have failed, it proposes new, evaluator-driven approaches designed to undermine the GDP’s dominance in the global market economy. Setting: The Stiglitz report commissioned in the wake of the 2008 financial crisis launched a ‘Beyond GDP’ movement. Since then, public alarm about the GDP growth addiction has escalated: the drawbacks of GDP as a free-market policy tool have become self-evident as the rich get richer, the ranks of the poor swell and the future of the planet hangs in the balance. Research Design: Not applicable. Data Collection and Analysis: For the twenty largest economies in the world, the article estimates climate change discounts to the GDP based on official CO2 emissions statistics and a social cost of carbon estimate derived from a 2015 survey of eminent climatologists. It also draws on composite indexes generated by four reputable social research organizations to rank countries for their contributions to the 5 Ps of the Sustainable Development Goals (SDGs): people, planet, prosperity, peace, and partnership. Findings: Pending the results of on-going efforts to upgrade worldwide statistics focused on the 169 SDG targets, the proposed GDP discounts help track progress towards the SDGs. But monitoring is not enough. In a policy world dominated by vested interests, the new ‘Beyond GDP’ indicators should be combined with principled, evaluator-directed evaluations.

This study seeks to empirically analyze Primary Mortgage Institutions (PMIs) Fundamentals and Gross Domestic Product Increase; in other words, economic growth in Nigeria. The (PMIs) fundamentals in the new PMIs guidelines include Mortgage finance, Investments and Deposits taking. Thus, PMIs Loans, PMIs Investments and PMIs Deposits are adopted as the explanatory variables and served as proxies for PMIs fundamentals to explain Gross Domestic Products (GDP). Data used for empirical estimation were sourced from CBN statistical Bulletin, 2011 and 2013 and analyzed using Multiple Regression technique parameters. The research findings were robust. The statistical parameters exhibited high coefficients and the F-statistics which indicates the overall significance of the model stood at 75.23. These results led us to reject the null hypothesis and accept the alternate hypothesis that there is a strong relationship between GDP and PMIs Loans, PMIs Investments and PMIs Deposits. However, the coefficients of the t-test parameters were low indicating that the impact of the explanatory variables on GDP was very minimal, meaning that their contributions to GDP were not relevant. Conclusively, the results indicate that while there is a significant relationship between GDP and PMIs variables, the impact of these variables on GDP was not significant during the period under review. Thus, we recommend that relevant policies with capacity to boost the activities of PMIs for maximum productivity should be enacted by government regulatory agencies in order to re-equip the housing finance market and increase the ratio of mortgage finance as a percentage of GDP.

In this paper, we aim to remark on the nine crucial economic factors that affect GDP (Gross Domestic Product) per capita as assess the importance, effect, or value of economic development for a sample of 31 years of economic data from Bangladesh for the period of 1992 to 2022. The research question is “What are the effects of these variables on GDP per capita?” To inquire into that business in detail we use multiple regression analysis in this paper as GDP (Gross Domestic Product) per capita is the regressand or dependent variable and the rest of the factors or variables are the regressors or independent variables. In this regard, we use nine independent variables in the regression analysis: Gross Domestic Product (GDP) in current billions of USD, GDP growth rate (latest) per annum, Inflation (on consumer price index), Gross Savings (%GDP), Literacy rate, Unemployment rate, Investment rate, Population growth rate, Poverty Rate. After the data analysis we found that among the nine independent variables, five have a significant impact on GDP per capita. For instance, Inflation (% of GDP), GDP (current USD), GDP growth rate, Gross Savings rate, and Poverty rate play a vital role in determining GDP per capita. Since we use time series data, to identify an accurate estimation as being present we test the stationarity of data, to conduct the time series has no unit root problem we use first difference and log difference such that the data and the estimation will become acceptable. An assortment of statistical tests, such as Normality Test, Multicollinearity, Heteroskedasticity, Autocorrelation, Goodness-of-Fit (GoF) Test, ANOVA (Analysis of Variance) Test, and Multiple Regression Analysis, were performed using GRETL (Gnu Regression, Econometrics and Time-series Library). We use CUSUM (cumulative sum) test and CUSUM (cumulative sum) square test to find out the stability of the coefficient or parameters. The research question is “What are the effects of these variables on GDP per capita?”

Can we live within environmental limits and still reduce poverty? Degrowth or decoupling?