The Rise and Fall of India’s Relative Investment Price: A Tale of Policy Error and Reform

India’s relative price of investment rose 44 percent from 1981 to 1991 and fell 26 percent from 1991 to 2006. We build a simple DGE model, calibrated to Indian data, in order to explore the impact of capital import substitution policies and their reform post-1991 in accounting for this rise and fall. Our model delivers a 23 percent rise before reform and a 31 percent fall thereafter. GDP per effective labor was 3 percent lower in 1991 compared to 1981 due to import restrictions on capital goods. Their removal, and a 71 percentage point reduction in tariff rates, raised GDP per effective labor permanently by 20 percent. (JEL E22, E23, F13, O11, O16, O19)

Determinants And Efficiency Level Of Capital Goods Imports In Indonesia : Exploring Using Gravity Models

The study aims to investigate the significant factors and efficiency of capital goods imports in Indonesia. This study applies the stochastic frontier gravity approach (SFGA) to explore Indonesia's capital goods import values. The results suggest that there are positive impacts of some factors on the capital goods imports, including the GDP and population of the trading partners, distance, and regional cooperation such as the Free Trade Agreement (FTA). However, some factors, including the exchange rate and some global crises have significant negative impacts on the capital goods imports. The positive effects of FTA on capital goods imports may contribute to a reduction in the behind-the-border constraints. Furthermore, the trade efficiency resulting from the model may suggest that there is still a gap between potential and actual trade affected by the country-specific constraints, implying the requirement to investigate the appropriate reforms in Indonesia to reduce such constraints. Penelitian ini bertujuan untuk mengetahui faktor signifikan dan tingkat efisiensi impor barang modal di Indonesia. Penelitian ini menggunakan pendekatan stochastic frontier gravity (SFGA) untuk mengeksplorasi nilai impor barang modal Indonesia. Hasil penelitian menunjukkan terdapat dampak positif dari beberapa faktor terhadap impor barang modal, antara lain PDB dan populasi mitra dagang, jarak, dan kerjasama regional seperti Free Trade Agreement (FTA). Namun, beberapa faktor, seperti nilai tukar dan beberapa krisis global berdampak negatif signifikan terhadap impor barang modal. Efek positif FTA pada impor barang modal dapat berkontribusi pada pengurangan hambatan di belakang perbatasan. Selain itu, efisiensi perdagangan yang dihasilkan dari model tersebut dapat menunjukkan bahwa masih ada kesenjangan antara perdagangan potensial dan aktual yang dipengaruhi oleh kendala khusus negara, yang menyiratkan kebutuhan untuk menyelidiki reformasi yang tepat di Indonesia untuk mengurangi kendala tersebut.

Liberalization

Liberalization is the removal of barriers to the cross-border movement of capital, goods, and people. Understanding liberalization is central to understanding how governments respond to and shape the global economy. This article reviews the literature on liberalization from a public-goods perspective, where liberalization is seen as benefiting the population as a whole, and from a private-goods perspective, where liberalization benefits a select few. These perspectives are united by questions over who supports liberalization, when liberalization occurs, and how governments liberalize markets. The article further explores the methods and approaches used by American International Political Economy (IPE), represented by articles published in International Organization, and British IPE, represented by articles published in the Review of International Political Economy.

The Impact of Covid 19 on Fisher and Fish FarmerTerms of Trade

Reflecting the level of welfare of the fishers and fish farmers, terms of trade index (namely NTN/NTP) is believed to have decreased as the result of the Covid 19 outbreak. And, recognizing the important role of fisheries in the economy, understanding what have occured to the index is relevant. This paper aimed to: (i) analyze the impact of the outbreak on NTN/NTPi and (ii) identify what changes in variables have significant contribution to the NTN/NTPi decrease. The analytical method used is descriptive quantitative. The primary data consisted of: (i) fisher and fish farmer terms of trade as published by the Central Bureau of Statistics, (ii) variables that compose the price index received by fishermen / fish farmers and the index of prices paid by fishermen / fish farmers. The results showed that the decline in NTN and NTP occurred in all provinces in Indonesia. For fishers and fish farmers, variables of received price index that had the most significant effect on the decline is basic need cost such as food, drinks, cloth and transportation while variables of paid price index that had the most significant effect on the decline is capital goods.

How do Capital Goods Index, Metal Index and Oil and Gas Index explain the rising Auto Index?

The automobile sector holds a noteworthy position in the Indian economy. Resurgence of the sector from the shortterm slump it experienced in 2019 and the advent of electronic vehicle revolution is certain to bring about remarkable changes in the industry. Additionally, sector’s image as a bellwether of economic conditions makes it an all the more intriguing sphere to study. The paper examines the relationship between auto index, capital goods index, metal index and oil and gas index. All the indices have followed an upward trajectory in the past years. The aim is to study if these movements are related to each other through tools of Johansen Tests of Cointegration and Vector Error Correction Model (VECM). The result confirms a long-run direct relationship between the auto index and capital goods index. However, such a relationship of the auto index with the other two indices in the study remains uncertain. The data does not clearly support a conclusion in their case. Keywords: Automobile sector, Indian economy, auto index, capital goods index, metal index, oil and gas index, VECM

A New Multi Echelon Repair Network Model with Multiple Upstream Locations for Level of Repair Analysis Problem

Level of repair analysis (LORA) determines (1) the best decision during a malfunction of each product component; (2) the location in the repair network to perform the decision and (3) the quantity of required resources in each facility. Capital goods have long life cycles and their total life cycle costs are extremely high. LORA, which can be done repeatedly during the life cycle of the product, both at design and product support phase, plays an important role in minimising the total life cycle costs of capital goods. It is mostly applied to systems that operate in different geographical areas and deployed in different regions, which include different subsystems with special technology and expertise, and have a complex product structure. In this study, we propose a new mathematical model to the LORA problem, which is more comprehensive and flexible than the other pure LORA models in the literature. The proposed model uses the multiple upstream approach that allows the transfer of the components from a location in the lower echelon to the predefined locations in the upper echelon and determines the material movement paths between each facility, defining the facilities’ locations in the repair network. The performance of the proposed model is tested on benchmark instances and the results are compared with the single upstream model. Computational experiments show that the proposed model is more effective than the single upstream model and reduces the total life cycle costs by 4.85% on average, which is an enormous cost saving when total life cycle costs of capital goods are considered.

Praktik Leasing di Indonesia dalam Tinjauan Hukum Islam

The development of leasing in Indonesia was in line with the development of banking, both bank and non-bank institutions. This development was certainly inseparable from the demands and needs of the community that they cannot fulfil on their own. The emerging financing institutions carry out activities in the form of providing funds or capital goods by not withdrawing funds directly from the public. The existence of leasing as a means for developing investment financing and empowering the community's economy was still considered to have several problems. Although the practice of leasing in Islamic law was equated with the contract of ijarah vomitiyah bi at-tamlik, in practice in Indonesia the process of leasing agreement was considered fasid, because there was an element of ambiguity in the contract agreement as regulated in the provisions of multi-aqad agreements, both conventional and sharia. This research will discuss the practice of financing in the community categorized as leasing under the provisions of applicable law and a review of Islamic law on the implementation of such leasing.

The Impact of ICT Investment and Diffusion on Economic Growth: Empirical Evidence from Rwanda

This study evaluates the influence of Information and Communication Technologies (ICT) investment and diffusion on Rwanda's economic growth. At the level we recommend, ICT imports greatly improve intermediate inputs to capital goods, resulting in increased economic growth. We use the most recent available data on technical innovation and investment for our empirical study, which spans the years 2005Q1 to 2020Q4. The results of regression analysis show that ICT development has little effect on Rwanda's economic growth. However, we notice a patchwork of information on ICT investment. We utilize ICT goods exports and imports as a proxy for ICT investment, based on previous research. Surprisingly, ICT goods exports have had no impact on Rwanda's economic growth. We do notice, however, that a 1% increase in ICT goods imports boosts economic growth by 3.9 percent. At this level, ICT goods import greatly boost the intermediate input to capital goods, resulting in increased economic growth. As a result, officials should ensure that ICT goods imports should be prioritized through supporting ICT investment to boost economic growth.

An Investigation of the Structural Characteristics of the Indian IT Sector and the Capital Goods Sector – An Application of the R Programming in Time Series Decomposition and Forecasting

<p>Time series analysis and forecasting of stock market prices has been a very active area of research over the last two decades. Availability of extremely fast and parallel architecture of computing and sophisticated algorithms has made it possible to extract, store, process and analyze high volume stock market time series data very efficiently. In this paper, we have used time series data of the two sectors of the Indian economy – Information Technology (IT) and Capital Goods (CG) for the period January 2009 – April 2016 and have studied the relationships of these two time series with the time series of DJIA indices, NIFTY indices and the US Dollar to Indian Rupees exchange rate. We established by graphical and statistical tests that while the IT sector of India has a strong association with DJIA indices and the Dollar to Rupee exchange rate, the Indian CG sector exhibits a strong association with the NIFTY indices. We contend that these observations corroborate our hypotheses that the Indian IT sector is strongly coupled with the world economy whereas the CG sector of India is the reflection of India’s internal economic growth. We also present several models of regression between the time series which exhibit strong association among them. The effectiveness of these models have been demonstrated by very low values of their forecasting errors. </p>

An Investigation of the Structural Characteristics of the Indian IT Sector and the Capital Goods Sector – An Application of the R Programming in Time Series Decomposition and Forecasting

<p>Time series analysis and forecasting of stock market prices has been a very active area of research over the last two decades. Availability of extremely fast and parallel architecture of computing and sophisticated algorithms has made it possible to extract, store, process and analyze high volume stock market time series data very efficiently. In this paper, we have used time series data of the two sectors of the Indian economy – Information Technology (IT) and Capital Goods (CG) for the period January 2009 – April 2016 and have studied the relationships of these two time series with the time series of DJIA indices, NIFTY indices and the US Dollar to Indian Rupees exchange rate. We established by graphical and statistical tests that while the IT sector of India has a strong association with DJIA indices and the Dollar to Rupee exchange rate, the Indian CG sector exhibits a strong association with the NIFTY indices. We contend that these observations corroborate our hypotheses that the Indian IT sector is strongly coupled with the world economy whereas the CG sector of India is the reflection of India’s internal economic growth. We also present several models of regression between the time series which exhibit strong association among them. The effectiveness of these models have been demonstrated by very low values of their forecasting errors. </p>