To analyze the effect of an increase in the quantity or quality of public investment on growth, this paper extends the World Bank’s Long-Term Growth Model (LTGM), by separating the total capital stock into public and private portions, with the former adjusted for its quality. The paper presents the LTGM public capital extension and accompanying freely downloadable Excel-based tool. It also constructs a new infrastructure efficiency index, by combining quality indicators for power, roads, and water as a cardinal measure of the quality of public capital in each country. In the model, public investment generates a larger boost to growth if existing stocks of public capital are low, or if public capital is particularly important in the production function. Through the lens of the model and utilizing newly-collated cross-country data, the paper presents three stylized facts and some related policy implications. First, the measured public capital stock is roughly constant as a share of gross domestic product (GDP) across income groups, which implies that the returns to new public investment, and its effect on growth, are roughly constant across development levels. Second, developing countries are relatively short of private capital, which means that private investment provides the largest boost to growth in low-income countries. Third, low-income countries have the lowest quality of public capital and the lowest efficient public capital stock as a share of GDP. Although this does not affect the returns to public investment, it means that improving the efficiency of public investment has a sizable effect on growth in low-income countries. Quantitatively, a permanent 1 ppt GDP increase in public investment boosts growth by around 0.1–0.2 ppts over the following few years (depending on the parameters), with the effect declining over time.

The objective of this study was to evaluate the growth of four lettuce cultivars in Southern Piauí to recommend the best ones for the region. The experiment was conducted in a greenhouse with randomized blocks, with evaluation in subdivided time plots, evaluated in six seasons (20, 24, 28, 32, 36, 40 days after sowing—DAS) and with treatments corresponding to four cultivars (Americana Rafaela^®, Grand Rapids TBR^®, Crespa Repolhuda^® and Repolhuda Todo ano^®) with five repetitions. Leaf area, number of leaves, collar diameter, aboveground fresh mass, aboveground dry mass, root dry mass and total and the physiological indices of growth analysis were evaluated. The lettuce cultivars interfered significantly in the studied parameters, being that Americana Rafaela^® and Repolhuda todo ano^®, in the conditions that they were submitted, presented better performances and bigger morphophysiological indexes, cultivated in pot. The cultivars Americana Rafaela^® and Repolhuda todo ano^® can be produced under the conditions of the south of Piauí.

Increasing water consumption has increased using of synthetic nutritional methods for enriching groundwater resources. Artificial feeding is a method that can save excess water for using in low level water time in underground. The purpose of this study is to evaluate the performance of the flood dispersal and artificial feeding system in the Red Garden of Shahr-e-Daghshan and improving, saving    quality of the groundwater table in the area. In order to investigate the performance of these plans, an area of 1570 km² was considered in the Southern of Shah-Reza. The statistics data from 5 years before the design of the plans (1986-2002) related to flood control fluctuations in 20 observation wells and many indicator Qanat were surveyed in this area. The annual fluctuations in the level of the station show a rise in the level of the station after the depletion of the plan. Dewatering of the first and second turns, with an increase of more than one meter above groundwater level, has had the highest impact on the level of groundwater table in the region. Reduced permeability at sediment levels, wasted flood through evaporation and wasteful exploitation of groundwater resources, cause to loss of the impact on the increase in the level and quality of groundwater in the area, especially in the dry, drought season and recent high droughts.

For five different regions in Kırklareli province, heavy metals; such as Pb, Ni, Cu, Mn, Cd, Cr, Co, Zn, Mo, and Fe in the mixture of leaves and flowers from linden trees (Tilia tomentosa L.) were analyzed by using flame atomic absorption spectroscopy after the samples were dissolved with microwave method. Also, organochloride pesticides; such as ∑BHC: [α-BHC, β-BHC, γ-BHC, and δ-BHC], ∑DDT: [4,4’-DDD, 4,4’-DDE, and 4,4’-DDT], α-Endosulfan, β-Endosulfan, Endosulfan sulfate, Heptachlor, Heptachlor-endo-epoxide, Aldrin, Dieldrin, Endrin aldehyde, Endrin ketone, Endrin and Methoxychlor in these samples were determined by utilizing gas chromatography mass spectroscopy after the samples were prepared for analyses by using QuEChERS method. The metal concentrations in the samples were in the range of 45.3 to 268 mg/kg for Mn, 0.25 to 18.8 mg/kg for Cu, 11.5 to 46.1 mg/kg for Zn, 128 to 1310 mg/kg for Fe, 10.4 to 38.6 mg/kg for Mo, 0.82 to 1.34 mg/kg for Cd, 0 to 6.45 mg/kg for Ni, 0 to 19.2 mg/kg for Pb, and 0 to 8.25 mg/kg for Cr. Moreover, the concentrations of organochloride pesticides in samples were usually determined to be lower than their maximum residue level values given the pesticide residue limit regulation of Turkish Food Codex. 

This exploratory study aims to identify the main characteristics and relationships between artificial intelligence (AI) and broadband development in Asia and the Pacific. Broadband networks are the foundation and prerequisite for the development of AI. But what types of broadband networks would be conducive are not adequately discussed so far. Furthermore, in addition to broadband networks, other factors, such as income level, broadband quality, and investment, are expected to influence the uptake of AI in the region. The findings are synthesized into a set of policy recommendations at the end of the article, which highlights the need for regional cooperation through an initiative, such as the Asia-Pacific Information Superhighway (AP-IS). 

Over the past decade, Ontario has seen a renewal in efforts to stimulate economic growth by investing in infrastructures. In this paper, we analyze the impact of public infrastructure investment on economic performance in this province. We use a multivariate dynamic time series methodological approach, based on the use of vector autoregressive models to estimate the elasticities and marginal products of six different types of public infrastructure assets on private investment, employment and output. We find that all types of public investment crowd in private investment while investment in highways, roads, and bridges crowds out employment. We also find that all types of public investment, with the exception of highways, roads and bridges, have a positive effect on output. The relatively large range of results estimated for the impact of each of the different public infrastructure types suggests that a targeted approach to the design of infrastructure investment policy is required. Infrastructure investment in transit systems and health facilities display the highest returns for output and the largest effects on employment and labor productivity. In terms of the nature of the empirical results presented here it would be important to highlight the fact that investments in health infrastructures as well as investments in education infrastructures are of great relevance. This is a pattern consistent with the mounting international evidence on the importance of human capital for long term economic performance.