Are there differences between unconditional and conditional demand estimates? implications for future research and policy

Background: Estimations of the demand for healthcare often rely on estimating the conditional probabilities of being ill. Such estimate poses several problems due to sample selectivity problems and an under-reporting of the incidence of illness. This study examines the effects of health insurance on healthcare demand in Indonesia, using samples that are both unconditional and conditional on being ill, and comparing the results. Methods: The demand for outpatient care in three alternative providers was modeled using a multinomial logit regression for samples unconditional on being ill (N = 16485) and conditional on being ill (N = 5055). The ill sample was constructed from two measures of health status – activity of daily living impairments and severity of illness – derived from the second round of panel data from the Indonesian Family Life Survey. The recycling prediction method was used to predict the distribution of utilization rates based on having health insurance and income status, while holding all other variables constant. Results: Both unconditional and conditional estimates yield similar results in terms of the direction of the most covariates. The magnitude effects of insurance on healthcare demand are about 7.5% (public providers) and 20% (private providers) higher for unconditional estimates than for conditional ones. Further, exogenous variables in the former estimates explain a higher variation of the model than that in the latter ones. Findings confirm that health insurance has a positive impact on the demand for healthcare, with the highest effect found among the lowest income group. Conclusion: Conditional estimates do not suffer from statistical selection bias. Such estimates produce smaller demand effects for health insurance than unconditional ones do. Whether to rely on conditional or unconditional demand estimates depends on the purpose of study in question. Findings also demonstrate that health insurance programs significantly improve access to healthcare services, supporting the development of national health insurance programs to address under-utilization of formal healthcare in Indonesia.health care demand; conditional estimates; unconditional estimates; health insurance

THE ROLE OF NATIVE LANGUAGE IN ENGLISH LEARNING AT SMAN 1 BANGKINANG SEBERANG

Bahasa Daerah adalah suatu bahasa selain dari Bahasa Inggris dan datang dari suatu lingkungan di mana suatu bahasa selain dari Bahasa Inggris adalah dominan. Bahasa Daerah adalah bahasa yang asli dari suatu area atau dapat disebut dengan bahasa lokal (Jean 2005: 4). Bahasa Daerah digunakan oleh orangorang dalam komunikasi sehari-hari dan pastinya orang-orang lebih memahami Bahasa mereka dibanding lain bahasa di dunia. Sekolah Menengah Atas Negeri 1 Bangkinang Seberang adalah salah satu dari sekolah dalam daerah Kampar. Sekolah Ini mempunyai lebih dari seratus para siswa, mereka adalah orang-orang Melayu daerah Kampar yang disebut dengan Orang Ocu. Mereka mempunyai suatu Bahasa Daerah dan disebut dengan Bahasa Ocu. Di samping, para siswa diajar Bahasa Inggris dalam kelas oleh guru Bahasa Inggris mereka dari daerah merekanya. Identifikasi Masalah adalah Apakah peranan Bahasa Daerah dalam pembelajaran Bahasa Inggris berpengaruh. Perumusan Permasalahan adalah apa peranan Bahasa Daerah dalam Pembelajaran Bahasa Inggris pada SMAN 1 Bangkinang Seberang? Sasaran hasil Studi adalah untuk menemukan dampak dari Bahasa Pribumi mereka dalam instruksi Bahasa Inggris. Didalam studi ini, harapan penulis adalah kepada guru bahasa Inggris SMAN 1 Bangkinang Seberang terutama, apa dampak Bahasa Daerah Dalam pengajaran Bahasa Inggris. Perancangan penelitian ini adalah penelitian deskriptif. Berdasarkan Lembar pertanyaan, persentase dari semua item dari Peranan Bahasa Daerah dalam Pembelajaran Bahasa Inggris adalah 44.4%% dan kriterianya tidak berpengaruh. Berdasarkan pada hasil itu dapat disimpulkan bahwa Peranan Bahasa Daerah itu tidak berpengaruh dalam pembelajaran Bahasa Inggris di Sekolah Menengah Atas Nomor 1 Bangkinang Seberang

Are there differences between unconditional and conditional demand estimates? implications for future research and policy

<p>Abstract</p> <p>Background</p> <p>Estimations of the demand for healthcare often rely on estimating the conditional probabilities of being ill. Such estimate poses several problems due to sample selectivity problems and an under-reporting of the incidence of illness. This study examines the effects of health insurance on healthcare demand in Indonesia, using samples that are both unconditional and conditional on being ill, and comparing the results.</p> <p>Methods</p> <p>The demand for outpatient care in three alternative providers was modeled using a multinomial logit regression for samples unconditional on being ill (<it>N </it>= 16485) and conditional on being ill (<it>N </it>= 5055). The ill sample was constructed from two measures of health status – activity of daily living impairments and severity of illness – derived from the second round of panel data from the Indonesian Family Life Survey. The recycling prediction method was used to predict the distribution of utilization rates based on having health insurance and income status, while holding all other variables constant.</p> <p>Results</p> <p>Both unconditional and conditional estimates yield similar results in terms of the direction of the most covariates. The magnitude effects of insurance on healthcare demand are about 7.5% (public providers) and 20% (private providers) higher for unconditional estimates than for conditional ones. Further, exogenous variables in the former estimates explain a higher variation of the model than that in the latter ones. Findings confirm that health insurance has a positive impact on the demand for healthcare, with the highest effect found among the lowest income group.</p> <p>Conclusion</p> <p>Conditional estimates do not suffer from statistical selection bias. Such estimates produce smaller demand effects for health insurance than unconditional ones do. Whether to rely on conditional or unconditional demand estimates depends on the purpose of study in question. Findings also demonstrate that health insurance programs significantly improve access to healthcare services, supporting the development of national health insurance programs to address under-utilization of formal healthcare in Indonesia.</p

MODELLING THE DEMAND FOR HEALTH CARE GIVEN INSURANCE: NOTES FOR RESEARCHERS

Understanding on health care demand given insurance givesprecious information to anticipate health care costs in the future,which in turn provides valuable information for policy makers,among other, to estimate claim rate, set up premium, designcost-sharing policy, etc. Unfortunately, estimating the effectsof health insurance on health care demand is not straightforward. This paper identifies crucial factors (e.g., adverseselection and provider behaviour) that need to be consideredin estimating the effects of health insurance on health caredemand. These considerations persuade researchers to usea rigorous econometric model in estimating health care demandgiven insurance with a view to isolate the true effects ofhealth insurance program. Such considerations can be furtherclassified into two-main factors. First is the features of thedependent variables used to measure the demand, and secondis the source of the data (or study design) used in the analysis.Keywords: modelling, health insurance, demand healthcareservices, applied econometric

Bukti Empiris Kebijakan Asuransi Kesehatan Sosial: Analisis Data Survei Aspek Kehidupan Rumah Tangga Indonesia (Sakerti)

Objective: Research that produced empirical evidences forhealth policy formulation presumably limited. This articleelaborates this perception by synthesizing four studies on thedemand for outpatient care (OP), e.g., (i) health insurance andthe number of OP visits, social health insurance and (ii) theuse of OP, (iii) providers choices, and (iv) equity in access.Methods: This study uses data from the second round of theIndonesian Family Life Survey (IFLS). Two considerations havebeen taken into account in selecting estimation methods: thedesign of observational study and type of the data used tomeasure the demand. To predict the number of OP visits, theauthor explored six count data estimators, whilst to investigatethe impact of social insurance on the use of OP, providerchoices, and equity, the author applied a multinomial logisticregression.Results: Whilst the distribution of health insurance isconcentrated on the rich, the highest effect of insurance onaccess found among the lowest income group. Given provideralternatives, the insured tend to choose public rather thanprivate providers. Those who are sicker, not married, wealthierand highly educated also prefer to use private than publicproviders. The impact of social insurance on equity in accessto health care was not observed.Conclusions: Efforts to increase access to health careservices through a national health insurance (NHI) will be moreeffective if the program accommodates consumer preferences.Changes in the demand from public to private providers mustbe taken into account, especially when setting premium subsidyand benefits baskets of the NHI. In general, the NHI policy hasalready empirical evidences. However, NHI implementationrequires a set of technical regulations as a translation of theNational Social Security Act, which also must be supportedfrom the results of empirical studies

Mengenal Rancang Bangun Program Keluarga Harapan Kesehatan

The Government of Indonesia is testing a conditional cash transfer (CCT) program, e.g., Family Hope Program. This program provides money to poor households conditional on investments in human capital. CCTs implementation in various countries has been followed by systematic efforts to measure their effectiveness and understand their broader impact on households\u27 behavior. The article shows empirical evidence that CCTs have improved the lives of poor people.CCTs have been hailed as a way of reducing inequality, especially in Latin America countries; helping households break out of a vicious cycle whereby poverty is transmitted from one generation to another; promoting child health and nutrition; and helping countries meet the Millennium Development Goals. This article explores more deeply on the design of the Indonesian CCT program, including the reasons for the development of CCT health and health conditionalitiesdetermination process

Estimasi Dampak Program Asuransi Kesehatan pada Jumlah Kunjungan Rawat Jalan di Indonesia

Background and method: This research aimed to selectthe best methods to predict the effect of health insuranceprogram on the numbers of outpatient visits in Indonesia. Theanalysis was applied to the second round of the IndonesianFamily Life Survey data (IFLS2).Result: The author compares the estimation results derivedfrom 6(six) econometrics technique count data model and selectthe best alternatives based on several statistics tests. Theresults confirm that Generalized Method of Moments (GMM)estimator is best to model the number of visits to public outpatient,whilst Hurdle Negative Binomial (HNB) is superior to model thenumber of visits to private one. It is proved that the insuredhave higher probability in the number of visits for outpatientservices then uninsured (p<1%). Supplies induce demandphenomena was not detected among the insured, howeverthis behaviour was likely happen where providers competitionare relatively high.Conclusions: This study concludes that estimates of healthcare demand given insurance have been shown to depend onthe empirical specification used in the analysis. Not controllingthe existence endogeneity of insurance leads to lower theparameter estimates. This study supports a national healthinsurance policy as an instrument to increase access to formalhealth care services.Keywords: health insurance, modeling, demand for health careservice

Modelling The Demand For Health Care Given Insurance: Notes For Researchers

Understanding on health care demand given insurance givesprecious information to anticipate health care costs in the future,which in turn provides valuable information for policy makers,among other, to estimate claim rate, set up premium, designcost-sharing policy, etc. Unfortunately, estimating the effectsof health insurance on health care demand is not straightforward. This paper identifies crucial factors (e.g., adverseselection and provider behaviour) that need to be consideredin estimating the effects of health insurance on health caredemand. These considerations persuade researchers to usea rigorous econometric model in estimating health care demandgiven insurance with a view to isolate the true effects ofhealth insurance program. Such considerations can be furtherclassified into two-main factors. First is the features of thedependent variables used to measure the demand, and secondis the source of the data (or study design) used in the analysis.Keywords: modelling, health insurance, demand healthcareservices, applied econometric

Pelembagaan Sistem Pemantauan dan Evaluasi: Pelajaran dari Berbagai Negara

This article provides lessons learned on the experience ofseveral countries that have succeeded in building a wellfunctioning government monitoring and evaluation (M&E)system. Discussions on this article are focused on: terms andconcepts in the field of M&E, outputs of M&E, utilization of M&Einformation, key success and pre-requisite to succes ininstitutionalizing M&E as well as actors M&E. The result indicatesthat ouputs of M&E system are used oftenly for: (i) supportingpolicy making, performance budgeting and national planning;(ii) helping ministries in their policy development and policyanalysis work, and in program development; (iii) managingactivities at the sector, program and project levels; and (iv)enhancing transparency and support accountabilityrelationships. The successful institutionalization of M&E involvesthe creation of a sustainable, wellfunctioning M&E system withina government, where good quality M&E information is usedintensively. This implies that key success for institutionalizingM&E system depends on: utilization of M&E information, qualityof M&E information and sustainability. Meanwhile prerequisiteto successful in institutionalizing of the M&E system must besupported by a substantive demand from the government,insentive mechanisms, powerful champion, and provision oftraining in a range of M&E tools, methods, approaches andconcepts. Actors involved in M&E system are not onlygovernment. Civil society (i.e., universities, NGOs, researchinstitutes, think tanks and the media) also can play a role inM&E in several ways, including as a user and producer ofM&E information

SURVEI SARANA PRASARANA DAN TENAGA PENGAJAR PENDIDIKAN JASMANI OLAHRAGA DAN KESEHATAN SMA NEGERI SE-KABUPATEN PONOROGO

Abstrak Sarana Prasarana dan Tenaga Pengajar merupakan fasilitas siswa untuk proses pembelajaran, dengan adanya fasilitas yang didapatkan siswa maka pembelajaran akan menjadi lebih baik dan dapat memperlancar jalannya proses pembelajaran. Penelitian dengan instrumen PDPJOI agar mempermudah peneliti untuk mengetahui hasilnya, karena didalam instrumen tersebut sudah tersedia nilai-nilai untuk mengetahui hasil penelitian. Populasi penelitian adalah SMA Negeri se-Kabupaten Ponorogo yang berjumlah 16 sekolahan. Di penelitian ini menggunakan metode kuantitatif untuk mengetahui kejadian yang sebenarnya ada di lapangan. Jenis penelitian ini ialah penelitian deskriptif untuk menggambarkan peristiwa yang sesungguhnya terjadi disekolah, dengan menggunakan penelitian ini kita dapat mengetahui sarana prasarana dan tenaga pengajar yang ada di sekolah. Hasil penelitian menunjukkan masih minimnya ketersediaan sarana dan prasarana sekolah dengan mendapatkan nilai C dengan rata-rata nilai 124 dari nilai maksimal 250, sedangkan untuk tenaga pengajar mendapatkan nilai A dengan rata-rata nilai 245 dari nilai maksimal 250. Penilaian tersebut diambil dan dirata-rata dari 16 sekolah yang ada di Ponorogo. Kata kunci: sarana prasarana, tenaga pengajar Abstract Infrastructure and teaching staff are students’ facilities for the learning process, with those facilities, the learning process will be better and it couldbe accelerated well. This study wasconducted with PDPJOI as the instruments in order to make it easier for the researchers to find out the results, sincethe values to find it out is already availablein these instruments. The population of this study was senior high schools in the district of Ponorogo, with the total number of 16 schools. This study used quantitative methods to find out the actual events in the field. The type of this research was descriptive research in order to describe the events that actually happened at school, by using this research we could find out the infrastructure and teaching staff at school. The results of the study showed that the availability of school facilities and infrastructure was still minimal by getting a C value with aaverage of 124 a maximum value of 250, while for the teaching staff getting an A with a average 245 of a maximum 250. The assessment was taken and on average from 16 schools in Ponorogo. Keywords: infrastructure, educational staf