The service sector is often associated with a countries economic's progress, where the more advanced a country, the greater its role in the service sector. Construction service is one of Indonesia's service sectors which has more than one forward and backward linkage value and shows that construction services are a key sector. However, the average growth of Indonesia's construction services exports during 2015-2020 was only 5.47 percent and still has the potential to be increased. Therefore, it is necessary to know the performance, comparative advantage, and competitive advantage of the construction services sector, which in turn needs to be formulated to increase the competitiveness of the sector. By using primary and secondary data, this study was analyzed using descriptive analysis, Export Product Dynamic (EPD), and Structural Equation Model (SEM). The results of the analysis show that the Indonesian construction services sector still has the opportunity to be developed as seen from the occurrence of excess demand, which indicates that the Indonesian construction market has not been fully exploited. The potential for developing exports of construction services with partner countries can be carried out by Indonesia with Australia, New Zealand, Japan, China, Korea, and several countries in Southeast Asia. The competitiveness of Indonesia's construction services sector is strongly affected by aspects of opportunity, regulation, and demand from partner countries. Therefore, several strategies that need to be carried out by Indonesia to increase the competitiveness of the construction services sector are determining priority partner countries, creating conducive conditions for political, security, economic, and business climate, strengthening and collaboration with Indonesian certification agency with the world of education, as well as strengthening business actors engaged in the service sector to be able to compete with competitors.
This paper examines the impact of institutional quality (government effectiveness index, voice and accountability index, and political stability) and economic variables (Gross Domestic Product [GDP], inflation, trade openness, and gross fixed capital formation) on Foreign Direct Investment (FDI) inflows in ASEAN 2012–2016 by using panel data analysis. The obtained results indicate that economics variables have a greater impact on FDI than political stability indicator. Our findings also suggest that insignificant effect of democracy and institutional quality indicator on FDI caused by the high level of corruption in ASEAN which maybe has a crowding out effect to level of democracy and institutional quality. ----------------------------------- Tujuan dari penelitian ini adalah untuk mengetahui pengaruh kualitas institusi (indeks government effectiveness, indeks voice and accountability, indeks stabilitas politik) dan variabel ekonomi lain (Gross Domestic Product [GDP], inflasi, keterbukaan perdagangan, dan gross fixed capital formation) terhadap Foreign Direct Investment (FDI) pada negara ASEAN periode tahun 2012–2016 dengan menggunakan analisis panel data. Hasil estimasi menunjukkan bahwa variabel ekonomi memiliki pengaruh yang lebih besar terhadap FDI dibandingkan dengan indikator stabilitas politik. Hasil kajian ini juga menemukan bahwa tidak signifikannya pengaruh indikator demokrasi dan kualitas institusi terhadap FDI dikarenakan tingginya tingkat korupsi yang mungkin memiliki efek crowding out terhadap tingkat demokrasi dan kualitas institusi.
Bea masuk merupakan salah satu komponen penerimaan pajak Indonesia yang terkena dampak signifikan akibat COVID-19. Kementerian Keuangan Republik Indonesia menyebutkan bahwa bea masuk mengalami kontraksi sebesar 13.5% pada tahun 2020, dan kemudian cenderung mengalami peningkatan pada tahun 2021. Dinamika yang cenderung volatile semacam itu tentu akan berpengaruh terhadap penentuan prioritas anggaran yang dilakukan oleh Kementerian Keuangan Republik Indonesia. Namun demikian, studi yang terkait dengan penerimaan bea masuk masih sangat terbatas dan sulit ditemukan. Oleh karena itu, studi ini menganalisa penerimaan bea masuk Indonesia selama periode 2016Q1-2021Q2 dan membuat model peramalan dengan menggunakan data realisasi penerimaan bea masuk bulanan. Hasil analisa menunjukkan bahwa model Auto Regressive Distributed Lag (ARDL) memiliki performa yang cukup baik untuk meramalkan bea masuk, dengan nilai MAPE pada in sample forecast sebesar 1.57%.
Kesenjangan harga merupakan masalah penting bagi Indonesia karena biaya transportasi dan biaya produksi. Harga cabai dan bawang merah relatif berfluktuasi antar waktu dan antar wilayah. Keduanya memiliki peran penting untuk dikonsumsi dan digunakan dalam industri makanan dan non-makanan. Pemerintah telah menerapkan beberapa kebijakan untuk mengurangi perbedaan harga antar daerah seperti tol laut dan infrastruktur: jalan, jembatan, dan sistem irigasi yang menggunakan dana desa. Studi ini meneliti hubungan atau kolerasi antara dana desa dengan perbedaan harga terhadap perbedaan harga di pasar cabai dan bawang merah di tingkat provinsi. Temuan menunjukan bahwa kesenjangan harga antar provinsi masih terjadi, terutama di wilayah timur dan barat. Papua adalah provinsi dengan harga cabai merah dan bawang merah tertinggi. Studi ini juga menemukan tidak ada korelasi antara dana desa dengan disparitas harga bawang merah dan cabai merah.
The economic performance of a country or region can be shown through various macro variables, including unemployment. The labor market is one part of the economic sector affected by the COVID-19 pandemic in addition to the health sector. Tangerang Regency is one of the region in Banten Province which is known as an industrial area and has a relatively large workforce. The purpose of this study is to analyze the effect of the COVID-19 pendemic on the open unemployment rate in Tangerang regency. This research method used are correlation analysis, Granger Causality and binary logistic regression model. Based on the results of the correlation analysis, it can be concluded that the district minimum wage (UMK) and the labor force have a significant and positive relationship with the unemployment rate and has moderate level of correlation, while based on the results of granger causality, it can be conclude that unemployment rate variable has a one way relationship with PDRB, UMK and the labor force. Variables that have a significant effect on reducing working hours during the pandemic are labor experience, experience squared, workings who work as argriculral, forestry, fisheries, operators and machine assembling workers, while the factors tha significantly affect the reduction in wages are labor status (married), age, age squared, profession (as manager, professional technician & assistant, service and sales personal, agricultural worker, forestry, fishery, processing worker, craft, machine operator and assembling, roug worker), essential sector and usage internet for work.
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