Análise regional do emprego dos municípios do Centro-Norte do Brasil nas primeiras décadas do Século XXI

This study aimed to investigate economic growth, regional economic pattern and structure of East Java Province. Other than that, this study also identified anddetermined superior sectors in East Java Province to give an illustration on which superior economic activities to be developed to improve the economic potential in East Java Province. Data employed in this study was secondary data in six years’ time series form 2010 until 2015 about GDP (Gross Domestic Product) for Indonesia, RGDP (Regional Gross Domestic Product) for East Java Province, total population in Indonesia, total population in East Java Province, the number of people living in poverty in Indonesia, and the number of people living in poverty in East Java Province. Data was obtained from Central Statistics Institution Indonesia, National Planning and Development Institution, Central Statistics Institution of East Java Province, and Regional Planning and Development Institution of East Java Province. Analysis tools used in this study included economic performance analysis, ShiftShare, Location Quotient (LQ), Growth Ratio Model (MRP) and Overlay analysis. The results of the study showed that: (1) economic performance index of East Java Province was quite good because during 2011-2015 the province got average economic performance index 0.847; (2) shift-share analysis showed that East Java Province economic showed an improvement during 2010-2015 by 340.769,50 billion rupiahs. Those economic performance improvements in East Java Province could be seen from the positive value of 16 (sixteen) economic activity sectors; (3) according to Location Quotient (LQ) analysis, there were five superior sectors in East Java Province, they were processing industry sector, water procurement sector, waste and recycle management sector, wholesale and retail, auto car and motorcycle reparation sector, accommodation and foods providing sector, and information and communication sector; (4) Growth Ratio Model analysis showed that sectors which had dominants growth and big contribution were construction sector, wholesale and retail, auto car and motorcycle reparation sector, transportation and warehousing sector, accommodation and foods providing sector, information and communication sector financial and insurance service sector, real estate sector, education service sector, health service and social activity sector; (5) Overlay analysis showed that potential economic sector in East Java Province included wholesale and retail, auto car andmotorcycle reparation sector, accommodation and foods providing sector, and information and communication sector; (6) weighing result according to Shift-Share Location Quotient (LQ), and Growth Ratio Model analysis were five sectors based on the highest rank of the most potential weighing result, they were accommodation and foods providing sector, processing industry sector, wholesale and retail, auto car and motorcycle reparation sector, information and communication sector, and construction sector.
 
 JEL Classification : P47, O47, C02, C02, C02, C02

The activity of extracting gems can be improved if public policies are adopted to expand the production chain in Brazil. In theory, the mining activity could be enhanced by increasing the financial collection of the taxes through mineral extraction aligned with the characteristics of the local economy. The present study uses a decision tree model for classifying the regional development of Brazilian states with gemstone mining activities, based on the regional data on financial compensation for mineral extraction (CFEM), gross domestic product (GDP), Human development index (HDI), environmental impact, and geo-tourism applying decision tree models. CFEM, HDP, HDI, and geo-tourism were continuous variables, and the environmental impact was discretized as ‘low,’ ‘medium,’ and ‘high.’ The results indicate that regional development is not only directly related to revenue from the financial compensation for mineral extraction. The GDP and environmental impact also influence regional development. The variables geo-tourism and HDI did not appear to exert influence on regional development. We infer that the increase in taxes would not directly benefit the local government or community from the results. Further initiatives and appropriate public policies would be necessary for planning the adequate distribution of the received resources from gem mining to improve regional growth and development.

Indonesia is the largest archipelago in the world with total land area is around 190 million hectares (ha), of which about 28.94 percent or some 55 million ha are agricultural land. As the world’s fourth most populous country, Indonesia’s total population is estimated to increase from about 245 million in 2013 to 288 million in 2050. This study aims to analyze the leading sectors of each province in Indonesia by Location Quotient (LQ) method and distribution of food security level in every province in Indonesia based on rice production balance. This research uses Gross Domestic Product (GDP) of Indonesia and Gross Domestic Regional Product of each of the provinces in all sectors during 2010-2014 obtained through the Indonesian Central Bureau of Statistics. The determination of the leading sectors of each province is based on the Location Quotient (LQ) which is the comparative method of the role of an economic sector in a province to the magnitude of the economic sector's role nationally. The food security index determined by the food security calculation that done by the ministry of Agriculture Indonesia especially the Food Security Agency of Indonesia based on the assumption of the resident who can fulfill more than 90 percent of Recommended Dietary Allowance (RDA) is food secure category. Leading sectors in Indonesia is varies between one province to other province. Leading sectors obtained from Location Quotient (LQ) formula shows that although it is said to be an agrarian country, the LQ results indicate that not all provinces in Indonesia have the leading sector in agriculture. Leading sector in agricultural is only found in 20 provinces out of 33 provinces in Indonesia (exclude North Kalimantan). Most provinces with agricultural based have experienced economic structuring towards secondary and tertiary sectors. Provinces with the highest LQ scores in agriculture, forestry and fisheries are found only in North Sumatra, Lampung, West Kalimantan, Central Sulawesi and West Sulawesi. Provinces with LQ> 1 score for the agricultural sector indicate that the province has a high level of agricultural production so that it becomes a comparative advantage for regional development. Agriculture, forestry and fishery sector still dominates in some parts of Indonesia, especially Sumatra, Sulawesi, Maluku, Nusa Tenggara and part of Kalimantan Island but not as major economic contributor. While most provinces in Java, Bali and Papua do not have an economic advantage in the agricultural sector. Food Security Index of Indonesia mainly classified as the moderate level except for North Maluku, Papua, and West Papua in low level and Bali and West Nusa Tenggara (NTB) in high level. Factors influencing differences in food security are based on availibility and affordability factors. Availibilty factor reflects the resilience of an area in terms of food availability, while affordability factor reflects the ease of obtaining food.

Gross Domestic Product (GDP) is general indicator used to identify the economical development in a region. The condition of economy in Central Java Province is categorized as stable condition since it has GDP value developed rapidly year by year. Refer to model used by Bappenas,the simultaneous equation model between GDP is influenced by number of employee and government spending.Identification of the model in this study using the ordercondition of indetification on the basis of the result of the overidentified taken the GDP of agriculture, mining, electricity, gas and water sector and trade. Therefore, the parameter evaluation used is 2SLS method (Two Stage Least Square). After fulfilled assumption of independent, identical and normal distribution, the most valued toward model of GDP in Central Java Province is GDP sector of agriculture.

Indonesia is one of the mineral rich developing countries in the world. Indonesia has a large quantity of mineral resources such as natural oil and gas, hard minerals (metallic, non metallic/industrial mineral, coal, and stone), because it is located in the Pacific ring of fire. Mineral and energy commodities have always been giving contribution to Gross Domestic Product (GDP) of Indonesia besides doing regional development, because of its potential mineral resources. Trade of mineral commodity aims is to gain from trade of mineral to increase economic growth through Balance of Trade (BOT). Mineral commodity markets have been volatile for a long time. The trends of mineral commodity prices have been fluctuated and recently it changed dramatically due to commodity prices to increase within only several years. The aims of this study are to comprehend recent contribution of mining sector to Indonesian economy 1990-2014 and to analyze forecasting of mineral commodity future prices until 2025. The price trends of commodity mineral is increasing from time to time, but sometimes decreasing because of world crisis, scarcity, and other problems in the world related to mining, trade, and relationship between countries, such as fundamentals matter, including long-run demand growth, technical change that opens up new sources of supply, changes that transform the operation of financial markets, and macro-economic shocks, etc. Mining sector contribute about 6-12% of Indonesian Gross Domestic Product and increasing from time to time. Contribution of mining includes trade of mineral commodity, regional development by companies, etc. It is shown that mining is important for Indonesian economy. Methodology applied in this paper is data analysis using dynamic commodity and macroeconomic models and forecast using linear and polynomial regression with its trend line.

Carbondioxyde emission is kind of green house gases that has highestconcentration in he atmosphere than the ohers green house gases. The aim of thisresearch is that analyzing influence of industry sector, mining sector, and transportationsector avtivities to the environment quality base on the carbondioxyde emission inIndonesia. This analysis used regression model with Ordinary Least Square method(OLS). Result of analysis indicate that Gross Domestic Product (GDP) of industry sectorhas negative and significant influence to carbondioxyde emission in Indonesia, with significant value at 0.00, Gross Domestic Product (GDP) of mining sector has positiveand significant influence to carbondioxyde emission in Indonesia with significant value at0.00 and Gross Domestic Product (GDP) of transportation sector has positive andsignificant influence to Economic Growth in Indonesia, with significant value at 0.00.Then, Gross Domestic Product (GDP) of industry sector, mining sector andtransportation sector have significantly influence to Economic growth in Indonesia withsignificant value at 0.00 based on with the theory Environmental Kuznet Curve (EKC).

Carbondioxyde emission is kind of green house gases that has highest concentration in he atmosphere than the ohers green house gases. The aim of this research is that analyzing influence of industry sector, mining sector, and transportation sector avtivities to the environment quality base on the carbondioxyde emission in Indonesia. This analysis used regression model with Ordinary Least Square method (OLS). Result of analysis indicate that Gross Domestic Product (GDP) of industry sector has negative and significant influence to carbondioxyde emission in Indonesia, with significant value at 0.00, Gross Domestic Product (GDP) of mining sector has positive and significant influence to carbondioxyde emission in Indonesia with significant value at 0.00 and Gross Domestic Product (GDP) of transportation sector has positive and significant influence to Economic Growth in Indonesia, with significant value at 0.00. Then, Gross Domestic Product (GDP) of industry sector, mining sector and transportation sector have significantly influence to Economic growth in Indonesia with significant value at 0.00 based on with the theory Environmental Kuznet Curve (EKC).

The mining industry plays a vital role in the economy of some Brazilian states. This research aims to evaluate the degree of influence of mining activity on the human development index (HDI) and the gross domestic product (GDP) in the Brazilian states of Bahia, Goiás, Minas Gerais, and Pará. The data used in the calculations were extracted from the Brazilian Institute of Geography and Statistics database from 2010 to 2020. Using the Pearson correlation method, we analyzed the impact of the mining economic activity on the regional income and HDI. The results showed a low correlation between gold mining production and HDI and GDP <i>per capita </i>indices of the states studied. It was found that Bahia State presented slight correlation rates (61.39% and 60.76%) for HDI and GDP <i>per capita</i>, respectively. The rates presented for the other states were below 35.00%, suggesting that mining activity does not influence the regional development of Goiás, Minas Gerais, and Pará. We concluded from the gold mining data that the mining industry did not impact regional development in the studied ten-year range. Further analysis should be carried out to verify the cost-benefit of gold mining, considering the environmental cost of mining activity.

The overall evolution of the economy is usually appreciated by two macroeconomic indicators GDP and GVA, which by their value gives us clear information on the state of the economy. Gross domestic product (GDP), the main macroeconomic aggregate of national accounts, is the final result of the production activity of resident producer units and which corresponds to the value of goods and services produced by these units for final consumption. Gross Value Added (GVA) is the balance of the production account and is measured as the difference between the value of the goods and services produced (valued at basic prices) and the intermediate consumption (valued at the buyer's prices), thus representing the new value created in the production process. GVA is calculated before calculating the consumption of fixed capital. Since 1990, we have been confronted with a major restructuring of the way GDP and GVA are created due to the intensive process of restructuring the economy. In the paper we will analyze the basis of the processing of national statistical data, how the tourism component of the tertiary sector contributes to the formation of the aggregate indicators presented above. In 2016, Romania had a GDP of 169.6 billion euros, below the Czech level (174.4 billion euros), Greece (175.9 billion euros) and Portugal (184.9 billion euros). Data series published by the European Statistical Office show that in the first quarter of this year, Romania's GDP adjusted for seasonal influences was 44.2 billion euros, while the value of GDP- Greece was 43.96 billion euros, the Czech Republic's 44.85 billion euros, and Portugal's 47.37 billion euros. In terms of GVA training, Romania is included in the European Union's Statistical Yearbook 201 6 as the country with the largest contributions to the Gross Value Added in the economy from industry, agriculture and construction, simultaneously with the lowest Public sector contribution (administration, defense, education, health and social welfare, etc.) Although professional, scientific and technical activities have seen the largest increase in the share of Gross Value Added training, they remain below the average of 10.4% Registered on the whole EU. There is an increase in the art, entertainment, recreation and other activities related to tourism - which brought us near the European customs and contributed to the "structural convection" of the Romanian economy. Touristic activity, particularly complex, with upstream and downstream implications, generates a tourism industry, whose components contribute to the formation of GDP and national Gross Value Added We will analyze the share of tourism in Romania's Gross Domestic Product in the period 2008-2014, gross value added in the tourism industry direct gross value added from tourism and gross domestic product of tourism in 2013 and 2014.
 
 Keywords: macroeconomic indicators, tourism industry, Gross Domestic Product, Gross Value Added economy

This study aims to analyze the mapping of potential, creative economy potential, review of the contribution of the creative industry, namely according to the value of Gross Domestic Product (GDP), based on Employment, and according to Company activities and increase economic growth in urban areas in Palembang. Based on the value of Gross Domestic Product (GDP), according to Employment, as well as based on Company activities and increasing economic growth of urban areas in Palembang. The research method used in this study means: Desk research sourced from the agency based on the value of Gross Domestic Product (GDP), based on employment, and based on activity. The company also increases the economic growth of urban areas in or related departments, namely the industrial department of Palembang City and literature on the creative industry using studies that are in accordance with the value of Gross Domestic Product (GDP), based on employment, as well as according to the Company's activities and increasing economic growth in urban areas. And a short survey to the creative industry was selected to receive primary data as an evidentiary activity supported by a structured survey tool. The mapping method used is the social mapping method.

Abstract. City/regional authorities are responsible to design and structure the urban morphology based on the desired land-use activities. One of the key concerns regarding urban planning is to establish certain development goals, such as Gross Domestic Product (GDP). In Canada, the gross national income mainly relies on mining and manufacturing industries. In order to facilitate new city development, this study aims to utilize remote sensing and GIS techniques to assess the relationship between the industrial area and the reported GDP in nine major cities in Canada. Free archive multi-temporal Landsat TM images and land use vector data were obtained for year 2005 and 2010 during the summer season, where the socio-economic data, such as GDP, population, and total employment are obtained from Metropolitan Housing Outlook for the same duration. The Landsat TM images were first atmospherically corrected and the built-up values were computed using the Normalized Difference Built-up Index (NDBI) and Normalized Difference Vegetation Index (NDVI) from the Landsat images. The high built-up values within the industrial areas were acquired for further analysis. Finally, a correlation analysis was conducted between the GDP, Population, and Total Employment with respect to the built-up areas. Preliminary findings show that the R2 between the percentage of built-up areas and industrial area within the corresponding city is 0.82. In addition, the R2 between the built-up areas and GDP ranges from 0.73 to 0.78. Consistent findings are observed in the similar correlation between the built-up areas and population, as well as the built-up areas and the employment, where the R2 is within 0.72 to 0.73. With the correlation found, we believe that results can be used as a generic indication for the federal/municipals authorities, which are aiming or target for a specific GDP with respect to the planned industrial area.

Identifying basic sectors and sub-sectors is one of stages to plan strategic area expansion for the centre of economy growth. Therefore, Location Quotient Analysis is needed to understand how far the level of specialization of economy sectors in particular area in utilizing its basis sectors or leading sectors. Basic sectors can be determined by using Location Quotient (LQ) method. Variables used to calculate basis economy are from local GDP of an activity focused on activities in the local economy structures. Gross Domestic Product (GDP) is an important indicator to understand economy condition particularly in Gorontalo Regency in particular period, either based on current prices or constant price. Data collection process done by using secondary data survey based on documents from Statistics of Gorontalo Regency and Statistics of Gorontalo Province. From 2012 up to 2016, processing industry sectors and service sectors have been stable basis in terms of improving LQ value and its GDP in an analysis period. This can be possible that those two sectors have contributed on the improvement of GDP of Gorontalo Regency including all other sectora that also become basis such as Mining and Excavation sector, agriculture sector and others.

As an important part of the comprehensive transportation system, air transportation is the key link connecting regional exchanges. And air transportation can actively promote the development of regional economy. In this paper, the airport operation and regional economy of the leagues and cities in Inner Mongolia are taken as the research object, the co-integration and Granger causality between the air passenger throughput (TQ) and regional gross domestic product (GDP) of the leagues and cities are analyzed, and the correlation between air passenger throughput and regional gross domestic product is discussed. It is found that there is co-integration relationship between the air passenger throughput and regional gross domestic product in seven cities. The League cities with co-integration relationship are Hohhot City, Ordos City, Baotou City, Tongliao City, Xilin Gol League, Hulunbuir City and Bayannur City. In Granger causality analysis, regional gross domestic product of Hohhot City, Baotou City, Hulun Buir City, Tongliao City, Chifeng City and Bayannur City, Xilin Gol League and Hinggan League is the Granger cause of air passenger throughput, and vice versa. regional gross domestic product and air passenger throughput of Ordos City are mutually Granger causality. In general, regional economic development plays a more significant role in promoting the growth of air transport. Through comparative study, it is found that regional economic development can better promote the growth of air transport in Tongliao City.

‘Dog Days’ Full Employment without Depreciation: Can It Be Done?

This research work centered on econometrics analysis on significance of transportation sector to the Nation Gross Domestic Product (GDP) in Nigeria economic. The aim of this research work is to test for significance of transportation sector to the Nation Gross Domestic Product. The literature review explains extensively on the important of using econometrics to carry out this research and why is desirable to fit the model. The methodology employs the use of multiple regression analysis, test of parameter and coefficient of determination. The road, sea, rail and air transportation are useful in predicting the value of Gross Domestic Product. The value of R-square show that combination of RT, ST, RailT and AT explain variation in GDP which is significantly implies that the four variables are important in GDP and the Sea transportation contribute majorly to the nation Gross Domestic Product. Testing the significant of the parameter, it is observed that there is presence of multicollinearity, heteroscedascity and autocorrelation and necessary correction are made on them.