Tropical deforestation continues at a very alarming rate. Certain forms of deforestation are economically desirable, but economic criteria alone are not sufficient for deciding whether a deforestation project is desirable. Previous studies on deforestation mechanisms are grouped into four general categories, i.e. Neo‐Malthusian, government‐failure, microeconomic and macroeconomic approaches. The Neo‐Malthusian approach sees population pressure as the underlying cause of tropical deforestation. The government‐failure approach looks at misdirected policies that result in unintended deforestation and government’s inability to preclude preventable deforestation. The microeconomic approach examines how, under various forms of market failure, an agent’s economic behaviours can lead to deforestation. The macroeconomic approach explores the possible links between debt and deforestation. We also present micro‐level evidence of a case where deforestation can be associated with farmers’ capital accumulation behaviour, and poverty is a deterrent to, not a cause of, deforestation.

Background To assess if physical distancing measures to control the COVID-19 pandemic can be relaxed, one of the key indicators used is the reproduction number R. Many developing countries, however, have limited capacities to estimate R accurately. This study aims to demonstrate how health production function can be used to assess the state of COVID-19 transmission and to determine a risk-based relaxation policy. Methods The author employs a simple “bridge” between epidemiological models and production economics to establish the cumulative number of COVID-19 cases as a short-run total product function and to derive the corresponding marginal product, average product, and production elasticity. Three crucial dates defining the states of transmission, labelled red, yellow, and green zones, are determined. Relaxation policy is illogical in the “red zone” and is not recommended in the “yellow zone”. In the “green zone”, relaxation can be considered. The Bayesian probability of near term’s daily cases meeting a policy target is computed. The method is applied to France, Germany, Italy, the UK, and the US, and to Indonesia as an example of application in developing countries. Results This study uses data from the WHO COVID-19 Dashboard, beginning from the first recording date for each country until February 28, 2021. As of June 30, 2020, France, Germany, Italy, and the UK had arrived at the “green zone” but with a high risk of transmission re-escalations. In the following weeks, their production elasticities were rising, giving a signal of accelerated transmissions. The signal was corroborated by these countries’ rising cases, making them leaving the “green zone” in the later months. By February 28, 2021, the UK had returned to the “green zone”, France, Germany, and Italy were still in the “yellow zone”, while the US reached the “green zone” at a very high number of cases. Despite being in the “red zone”, Indonesia relaxed its distancing measures, causing a sharp rise of cases. Conclusions Health production function can show the state of COVID-19 transmission. A rising production elasticity gives an early warning of transmission escalations. The elasticity is a useful parameter for risk-based relaxation policy.

BackgroundPhysical distancing measures to control the COVID-19 pandemic come at a heavy short-term economic cost. But easing the measures too early carries a high risk of transmission re-escalations. To assess if physical distancing can be relaxed, a number of epidemic indicators are used, most notably the reproduction number R. Many developing countries, however, have limited capacities to estimate R accurately. This study aims to demonstrate how health production function can be used to assess the state of COVID-19 transmission and to determine a risk-based physical distancing relaxation policy.MethodsThe author establishes a short-run health production function, representing the cumulative number of COVID-19 cases, from the standard SIR model. Three zones defining the state of transmission are shown. The probability of meeting a policy target, given a production elasticity range, is computed. The method is applied to France, Germany, Italy, the UK and the US, and to Indonesia as an example of application in developing countries. ResultsAs of June 30, 2020, France, Germany, Italy and the UK have arrived in the “green zone” where relaxation can be considered. The US is still in the “red zone” where physical distancing still needs to be applied. France, Germany and Italy can set a policy target of maximum daily-cases of 500, while the UK has to make do with a target of 1,100 daily-cases. France, Germany, Italy and the UK still exhibit a relatively high risk of their daily-cases failing to meet the policy target or even rising. Indonesia is still in the “red zone”, so it comes as no surprise that the country’s daily-cases rose sharply after relaxation of physical distancing. ConclusionsShort-run health production function can be used to assess the state of COVID-19 transmission and to determine a risk-based physical distancing relaxation policy. Given its simplicity and minimum data requirement, the approach is very useful for developing countries which are unable to have reliable estimates of the reproduction number R. Follow-up research from this study may include estimating an economically optimal date for relaxing distancing measures and application of this method to other epidemics.

Political economy concerns with how actual policies deviate from economic optimality. This study evaluates Indonesia’s progresses toward sustainable development goals (SDGs) from the political economy viewpoint.  The authors discuss Indonesia’s Voluntary National Reviews (VNRs) and critically analyse its COVID-19 pandemic control policy given the policy’s importance to SDG 3 (good health and well-being) and SDG 8 (decent work and economic growth).  Indonesia  chooses  to opt-out strict  public  health  restrictions  because  of the government’s preoccupation with economic  growth, the large number of  workers relying on daily income and its state of democratic consolidation. This  results in  Indonesia’s failure to control the pandemic and to avert economic recession. Indonesia correctly anticipates global vaccine nationalism and secures adequate vaccine supplies primarily from China. Vaccination becomes Indonesia’s key pandemic strategy. This  study shows how indispensable partnerships (SDG 17) are for achieving SDGs, presenting the case of the Indonesian Forestry Certification Cooperation’s work in forest certification and sustainable forest management.

This study aims to analyze the effect of third-party funds, non-performing loans, loan-to-deposit ratio, net interest margin, and operating-income-to-operating-expenses on the growth of working capital loans disbursement in the Indonesian banking industry. Making use of the purposive sampling technique, thirteen out of a population of forty six conventional commercial banks listed in the Indonesian Stock Exchange were selected as this study’s samples. Quantitative secondary data obtained from these banks’ annual reports of 2011-2019 were analyzed by use of the panel data regression method with a fixed effect approach. The results show that third-party funds, loan-to-deposit ratio, net interest margin, and operating-expenses-to-operating-income have a statistically significant positive effect on the growth of of working capital loans. Non-performing loans is shown to have a statistically non-significant effect on working capital loans growth.