Kenya in Motion 2000-2020

This edited volume offers a broad understanding and particular visions of Kenya in the first quarter of the twenty-first century. By bringing together rigorous yet accessible contributions, it shows how, since the 2002 transition, Kenya has been striving for change through economic modernisation and political liberalisation. The planned transformations are coming to fruition, even if the legacies of the past and political habits are slowing down the process. The various chapters take us from developmental capitalism to extreme poverty and enduring inequalities, from reforms on paper to mixed results in multiple sectors: decentralised governance, natural resources, land, and education. They also explore Kenya’s ancient and colonial history and the diversity of its population. Thus, the book helps understand contemporary political, religious and community cleavages, the asymmetries between towns and the countryside, between Nairobi and the coast, in a country open to the world, as much through trade and finance as through art networks

IMPORTANCE OF CAP REFORMS FOR THE DUTCH AGRICULTURAL SECTOR IN 2000-2020

Since 2000, the two important reforms of The EU Common Agricultural Policy (CAP) took place. The Agenda 2000 Berlin Agreement of March 1999 aimed to increase EU agriculture market orientation and focuses on the grain, oilseed, dairy and the beef sectors. It reduced intervention prices in these sectors and lowered the set-aside requirements for crops and by implementation of non-crop specific compensatory payments. The core of The Luxembourg Agreement from June 2003 was an acceleration of decoupling of farm support initiated by the Agenda 2000 complementary payment. It introduces a system of direct payments (known as single payment scheme - SPS), which are no longer linked to the production (decoupling). This CAP reform also includes commodity specific measures, especially in dairy sector. The Luxemburg Agreement links the direct payments to farmers with farm management practices which maintain environmental and other requirements set at EU and national levels (‘Cross-compliance’). The goal of this paper is twofold. First, we investigate the impact of the CAP reform on the Dutch agricultural sector in 2004 – 2007; second we examine effects of possible future CAP reform decision on the Dutch agriculture till 2020. The study is based on the AGMEMOD econometric model developed within the framework of projects financed by the European Commission. It reflects a sectoral, dynamic, partial equilibrium model, which takes into account the national specificities and is built up of models for the Member States of the EU27. The foundation for AGMEMOD is laid in the establishment of country model templates, which must achieve compatibility of the models to be built and the communality of data. The most important differences between the national models are macroeconomic assumptions, components of policies under the CAP and SAPS (in respect with the new Member States) and assumptions on the impact of direct payments on agricultural production (degree of decoupling). On the country level, commodity templates must encapsulate the modeling system to be used. Many components of these templates are based on the information and guidelines delivered by Hanrahan (2001), but then adapted to country-specific conditions. At least, they must contain issues on market and policy description, flow charts, key market and specification of the functional forms of the commodity model. The AGMEMOD model covers all important CAP commodities: grains, oilseeds, potatoes, sugar and sugar beets, livestock products, milk and dairy products. We will investigate the CAP impact on the Dutch agriculture by mean of policy simulations with the Dutch AGMEMOD model. To isolate policy effect in the historical period 2000 - 2007, counterfactual simulations for 2000 - 2007 will be run. To simulate the response of the Dutch agriculture on different policy changes in 2008 - 2020, the no-policy change baseline scenario will be developed and several policy experiments will be conducted: milk quota abolition, biofuel directive implementation and animal premiums decoupling. To indentify the policy effects the policy scenarios will be compared with the baseline.CAP, CAP Reform, Dutch agriculture, Agricultural and Food Policy, Research Methods/ Statistical Methods, Q10, Q18,

Analisis sektor industri manufaktur di Indonesia

because it can increase economic growth. This study aims to analyze the factors that affect the manufacturing industry sector in Indonesia. The analytical method used in this research is descriptive analysis and quantitative analysis. Overall, from 2000 - 2020, the average development of the manufacturing industry was 12.67 percent, labor averaged 2.4 percent, investment averaged 9.2 and inflation averaged 8.6 percent. This study uses multiple linear regression analysis using the period 2000-2020. The results of the study show that the variable Number of Labor and investment has an effect on the manufacturing industry in Indonesia for the period 2000-2020, while inflation has no effect

Global air quality inequality over 2000-2020

Air pollution generates substantial health damages and economic costs worldwide. Pollution exposure varies greatly, both between countries and within them. However, the degree of air quality inequality and its' trajectory over time have not been quantified at a global level. Here I use economic inequality indices to measure global inequality in exposure to ambient fine particles with 2.5 microns or less in diameter (PM2.5). I find high and rising levels of global air quality inequality. The global PM2.5 Gini Index increased from 0.32 in 2000 to 0.36 in 2020, exceeding levels of income inequality in many countries. Air quality inequality is mostly driven by differences between countries and less so by variation within them, as decomposition analysis shows. A large share of people facing the highest levels of PM2.5 exposure are concentrated in only a few countries. The findings suggest that research and policy efforts that focus only on differences within countries are overlooking an important global dimension of environmental justice

Does Age Structure Forecast Economic Growth?

High ratios of working age to dependent population can yield a increases the rate of economic growth. We estimate the parameters model with a cross section of countries over the period 1960 to 1980 inclusion of age structure improves the model’s forecasts for the period that including age structure improves the forecast, although there instability between periods with an unexplained growth slowdown the model to generate growth forecasts for the period 2000–2020.Economic Growth, demography, forecast, evaluation, error decomposition

Analisis Trend Perkembangan Volume Impor Daging Sapi di Indonesia Selama Periode Tahun 2000–2020 dan Faktor-Faktor yang Mempemgaruhinya

       Tujuan dari penelitian ini untuk mengetahui trend perkembangan volume impor daging sapi di Indonesia selama periode tahun 2000-2020, untuk mengetahui pengaruh harga daging sapi impor,harga daging dalam negeri, konsumsi daging sapi, produksi daging sapi, dan nilai tukar rupiah di Indonesia selama periode tahun 2000-2020. Metode yang digunakan yaitu metode analisis data sekunder dengan data tahunan (time series). Hasil analisis pengaruh harga daging sapi impor dan harga daging sapi dalam negeri terhadap volume impor daging sapi menunjukkan bahwa adanya pengaruh yang signifikan (nyata), analisis pengaruh konsumsi daging sapi terhadap volume impor daging sapi menunjukkan bahwa tidak adanya pengaruh yang signifikan (nyata), analisis pengaruh produksi daging sapi terhadap volume impor daging sapi menunjukkan bahwa tidak adanya pengaruh yang signifikan (nyata), dan analisis pengaruh nilai tukar rupiah terhadap volume impor daging sapi menunjukkan bahwa tidak adanya pengaruh yang signifikan (nyata). Trend perkembangan volume impor daging sapi di Indonesia selama periode tahun 2000-2020 mengalami kecenderungan meningkat

A model of osteoporosis impact in Switzerland 2000-2020

The aim of our study was to develop a modeling framework suitable to quantify the incidence, absolute number and economic impact of osteoporosis-attributable hip, vertebral and distal forearm fractures, with a particular focus on change over time, and with application to the situation in Switzerland from 2000 to 2020. A Markov process model was developed and analyzed by Monte Carlo simulation. A demographic scenario provided by the Swiss Federal Statistical Office and various Swiss and international data sources were used as model inputs. Demographic and epidemiologic input parameters were reproduced correctly, confirming the internal validity of the model. The proportion of the Swiss population aged 50 years or over will rise from 33.3% in 2000 to 41.3% in 2020. At the total population level, osteoporosis-attributable incidence will rise from 1.16 to 1.54 per 1,000 person-years in the case of hip fracture, from 3.28 to 4.18 per 1,000 person-years in the case of radiographic vertebral fracture, and from 0.59 to 0.70 per 1,000 person-years in the case of distal forearm fracture. Osteoporosis-attributable hip fracture numbers will rise from 8,375 to 11,353, vertebral fracture numbers will rise from 23,584 to 30,883, and distal forearm fracture numbers will rise from 4,209 to 5,186. Population-level osteoporosis-related direct medical inpatient costs per year will rise from 713.4million Swiss francs (CHF) to CHF946.2million. These figures correspond to 1.6% and 2.2% of Swiss health care expenditures in 2000. The modeling framework described can be applied to a wide variety of settings. It can be used to assess the impact of new prevention, diagnostic and treatment strategies. In Switzerland incidences of osteoporotic hip, vertebral and distal forearm fracture will rise by 33%, 27%, and 19%, respectively, between 2000 and 2020, if current prevention and treatment patterns are maintained. Corresponding absolute fracture numbers will rise by 36%, 31%, and 23%. Related direct medical inpatient costs are predicted to increase by 33%; however, this estimate is subject to uncertainty due to limited availability of input dat