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Record ID: 105 [ Page 6 of 16, No. 1 ]
Performance Evaluation and Comparison of Integer- Valued Time Series Models for Measles Outbreak Detection in Cavite
Authors: Vio Jianu C. Mojica and Frumencio F. Co
Abstract:
An ideal outbreak detection algorithm must be able to generate alarms early into an outbreak while providing optimal sensitivity and specificity so as to mitigate mortality and other potential costs of investigation and response to these events. One particular disease of interest is measles, which is a highly contagious disease that exhibited periodic outbreaks in the Philippines. The performance of the NGINAR(1) and ZINGINAR(1) models for measles outbreak detection was examined through the use of simulated datasets and an actual application to reported measles cases in the Cavite province from 2010 to 2017. The models were evaluated based on their goodness-of-fit as well as the sensitivity, specificity, and timeliness of the detection thresholds they have generated. Comparisons were done against ARIMA models and the popular Poisson INAR(1) model. Results show that INAR models have considerably higher probabilities of detection than ARIMA models, particularly for outbreaks of small magnitudes. The Poisson INAR(1) generates the most alarms and thus, has the highest sensitivity metrics. The NGINAR(1) and ZINGINAR(1) models, however, have lower false positive rates with outbreak detection capabilities comparable to the Poisson INAR(1). The NGINAR(1) model may be chosen as the best model considering its simplicity and its balance of sensitivity, specificity, and timeliness which is optimal for a disease such as measles.
Keywords: NGINAR(1), ZINGINAR(1), measles, outbreak detection, Cavite
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Year: 2019 Vol.: 68 No.: 1
Record ID: 114 [ Page 6 of 16, No. 2 ]
Investigating Dissimilarity in Spatial Area Data Using Bayesian Inference: The Case of Voter Participation in the Philippine National and Local Elections of 2016
Authors: Francisco N. de los Reyes
Abstract:
A commonly studied characteristic of area data is the assessment of similarity (or absence thereof) among neighboring areal units. However, most methodologies do not measure uncertainties which are likely outcomes of sampling variation and do not consider spatial autocorrelation. This paper explores the ability of Bayesian modeling to address the said situations. It attempts to apply this modeling technique to the voting participation statistics in the Philippine National and Local Elections of 2016.
Keywords: conditional autoregressive (CAR), proximity matrix, dissimilarity, voter turnout
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Year: 2018 Vol.: 67 No.: 1
Record ID: 113 [ Page 6 of 16, No. 3 ]
Measuring Market Risk with the Folded Peaks-Over-Thresholds Approach
Authors: Peter Julian Cayton
Abstract:
In this paper, we discuss the folding procedure for the peaks-overthresholds (POT) models and their applications in market risk measurement, namely the value-at-risk (VaR) and the expected shortfall (ES). Folding is deï¬ned as a procedure in which when data fall below a certain threshold value, a transformation formula will move the data points above the threshold. First, an initial ï¬tting with the generalized Pareto distribution (GPD) over a temporary threshold is done. Second, from the initially-ï¬tted GPD estimates and a newly-selected threshold, a folding transformation of moves the data points lower to the new threshold to higher values. Third, the data points higher than the new threshold are ï¬t to the GPD for inference and risk estimation. The risk measures from the folded GPD approach are compared with the ARMA-GARCH ï¬nancial econometric and the unfolded POT approach in terms of their performance in real ï¬nancial time series data such as the stock indices and foreign currencies. The beneï¬t of folding in the POT approach is lower estimates of standard errors for the GPD parameters given that an appropriate threshold has been selected. These would indicate more accurate GPD parameter estimates that lead to better VaR and ES estimates. The real data application results show that the VaR and ES from the folded POT methodology have less exceedances. Loss calculations indicate that those folded POT might mean higher capital adequacy, the conservatively set VaR and ES would cushion from extreme losses incurred from exceedance events.
Keywords:
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Year: 2018 Vol.: 67 No.: 1
Record ID: 112 [ Page 6 of 16, No. 4 ]
Employment Correlates of Multidimensional Poverty in the Philippines
Authors: Manuel Leonard Albis and Jessmond Elviña
Abstract:
Multidimensional poverty index (MPI) captures more welfare characteristics than the income- or expenditure-based poverty measures. It is an emerging social statistic, which must be understood to guide poverty alleviation policies. This paper finds robust employment characteristics on MPI using Bayesian averaging of classical estimates (BACE). The results indicate that being employed decreases MPI but length and nature of employment add to the MPI. Community public goods, as well as remittances, decrease the MPI, among other control variables considered. Priority through uplifting policy measures should be given more to laborers who are working for different employers than contractual workers if the aim is to reduce MPI.
Keywords: MPI, underemployment, BACE
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Year: 2018 Vol.: 67 No.: 1
Record ID: 111 [ Page 6 of 16, No. 5 ]
Coping with Disasters Due to Natural Hazards: Evidence from the Philippines
Authors: Majah-Leah Ravago, Dennis Mapa, Jun Carlo Sunglao and James Roumasset
Abstract:
We explored how local governments respond to disasters due to natural hazards to determine the mix of risk management and coping strategies (ex ante and ex post) they employ to improve welfare. We focused on disasters caused by hydro-meteorological hazards that occur with high frequency and high probability. Using data from a novel survey we conducted on disaster risk management practices of local government units (LGUs) in the Philippines, we developed indices of the various risk management and coping strategies of LGUs to explain what aids in their recovery from disasters. The most prominent strategies are risk-coping activities, especially cleanup operations and receiving relief from others. Among ex ante activities, employing long-term precautionary measures improve recovery. These include building resilient housing units; investing in stronger public facilities; building dams, dikes, and embankments; upgrading power and water lines; maintaining roads; identifying relocation areas; and rezoning and land-use regulations. In contrast, interruption of lifeline services such as water and electricity contributes adversely to recovery. Evidence also shows that LGUs’ profile characteristics matter. An LGU with higher local revenues has higher chances of recovery. On the other hand, being located in a province where dynasty share is high contributes negatively to an LGU’s recovery. The combination of these ex ante and ex post risk management strategies informs policies on where to put priority and investments in disaster risk management.
Keywords: Disaster, shock, coping, risk management, local government
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Year: 2018 Vol.: 67 No.: 1
Record ID: 110 [ Page 6 of 16, No. 6 ]
The Multidimensional Approach to Measuring Poverty
Authors: Lisa Grace S. Bersales, Divina Gracia L. del Prado and Mae Abigail O. Miralles
Abstract:
The current official measurement of poverty published by the Philippine Statistics Authority is based on income. This does not capture the multidimensional deprivations suffered by Filipinos. This paper discussed a multidimensional poverty index (MPI) for the Philippines using four (4) dimensions with thirteen (13) indicators. These dimensions are education; health and nutrition; housing, water and sanitation; and employment. The Alkire Foster (AF) method in computing multidimensional poverty measures is adopted with nested uniform weights as the weighting scheme and 1/3 as poverty cutoff. Various weighting schemes are also explored in this study - nested inverse incidence and subjective welfare, and other poverty cutoffs studied are 1/4 and 1/5. Results revealed that the selection of weighting scheme and poverty cutoff do not greatly affect the trend of the multidimensional poverty measures and the ranks of the dimensions in terms of their contribution to multidimensional poverty.
Keywords: multidimensional poverty, MPI, poverty, headcount ratio, intensity
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Year: 2018 Vol.: 67 No.: 1
Record ID: 104 [ Page 6 of 16, No. 7 ]
Economic Mobility in Urban Southeast Asia: The Case of the Philippines and Indonesia
Authors: Novee Lor Leyso, Arturo Martinez Jr., and Iva Sebastian
Abstract:
Recognizing that urban areas play a key role in addressing poverty and inequality in line with the Sustainable Development Goals (SDGs) 1 and 10, respectively, it is necessary to understand the dynamics of economic well-being of people living in urban areas to be able to formulate appropriate and effective strategies. Using economic mobility as a metric of well-being, this study aims to examine whether population size of urban areas has an impact on people's mobility prospects. We investigate this issue using longitudinal expenditure data from Indonesia and the Philippines. Our results show that city size has mixed effect on directional mobility in Indonesia and the Philippines; it has a negative but significant impact on the probability of Indonesians to experience upward mobility, but its effect on the probability of Filipinos to experience upward mobility is positive. On the other hand, in both countries, people living in megacities and micro urban areas experience more non-directional mobility with respect to several economic mobility measures.
Keywords: Economic mobility, Urbanization, Urban Poverty, Inequality, City Size, Panel Data, and Multinomial Logistic Regression
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Year: 2017 Vol.: 66 No.: 2
Record ID: 103 [ Page 6 of 16, No. 8 ]
Understanding the Ideal Number of Children and Contraceptive Practices of Filipino Women through Generalized Linear Models
Authors: Isabella Benabaye, Patricia Rose Donato and John D. Eustaquio
Abstract:
In making and assessing family planning policies and programs, it is vital to investigate fertility preference as it does not only reveal a woman's ideal number of children and the couple's consensus on it, but also captures information on unwanted and mistimed pregnancies. The theoretical relationships of a woman's ideal number of children with micro-level factors such as a woman's experience with child mortality, her level of household authority, and household family planning awareness were examined under two cases. First, among women who have achieved their fertility preference, and secondly, among women who have not achieved their fertility preference. This study also examined the factors affecting the contraceptive behavior of women who have not achieved their fertility preference, specifically for a) contraceptive users, b) non-users who intend to use contraceptives later, and c) non-users with no intention to use. The difference in the behavior of factors influencing the ideal number of children between women who have and have not met their fertility preference showed that instead of factors related to family planning, the ideal number of children for women with unmet fertility preference is decreased by factors that suggest lack of women's empowerment. On the other hand, analysis on contraceptive behavior found possible factors that can hinder the realization of women's intention to practice contraception.
Keywords: fertility preference, contraceptive behavior, poisson count model, binary regression
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Year: 2017 Vol.: 66 No.: 2
Record ID: 102 [ Page 6 of 16, No. 9 ]
Measles Outbreak Detection in Metro Manila: Comparisons between ARIMA and INAR Models
Authors: Joshua Mari J. Paman, Frank Niccolo M. Santiago, Vio Jianu C. Mojica, Frumencio F. Co, and Robert Neil F. Leong
Abstract:
It is the goal of many developing countries to stop the spread of diseases. Part of this effort is to conduct ongoing surveillance of disease transmission to foresee future epidemics. However, in the Philippines, there is a lack of an automated method in determining their presence. This paper presents a comparison between an integer-valued autoregressive (INAR) model and the more commonly known autoregressive integrated moving average(ARIMA) models in detecting the presence of disease outbreaks. Daily measles reports spanning from January 1, 2010 to January 14, 2015 were obtained from the Department of Health and were used to motivate this study. Synthetic datasets were generated using a modified Serfling model. Similarity tests using a dynamic time warping algorithm were conducted to ensure that simulated datasets observe similar behavior with the original set. False positive rates, sensitivity rates, and delay in detection were then evaluated between the two models. The results gathered show that an INAR model performs favorably compared to an ARIMA model, posting higher sensitivity rates, similar lag times, and equivalent false positive rates for three-day signal events.
Keywords: measles, biosurveillance, integer-valued autoregressive model, Serfling model, dynamic time warping
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Year: 2017 Vol.: 66 No.: 2
Record ID: 101 [ Page 6 of 16, No. 10 ]
Modeling Rare Events using a Zero-Inflated Poisson (ZIP) Distribution: Some New Results on Point Estimation
Authors: Suntaree Unhapipat, Nabendu Pal and Montip Tiensuwan
Abstract:
This paper takes a fresh look on point estimation of model parameters under a Zero-Inflated Poisson (ZIP) distribution. The reason is that some finer details of point estimation, if overlooked, may lead to wrong estimates as was done by the earlier researchers. In this paper we have achieved the following new results: (a) A new set of corrected method of moments estimators has been proposed; (b) We have shown how the standard technique of differentiating the log-likelihood function to find the maximum likelihood estimators may lead to wrong estimates, as well as how to avoid this problem; and (c) A new adjusted maximum likelihood estimation technique has been proposed which not only produces meaningful estimates always, but also appears to work better compared to all other estimation techniques in terms of standardized mean squared error (SMSE) when ZIP is used to model rare events. Finally, datasets on rare events have been used to demonstrate the estimation techniques, and how the ZIP distribution can be used to model such datasets.
Keywords: Maximum likelihood estimation, method of moments estimation, standardized mean squared error, standardized bias, goodness of fit test.
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Year: 2017 Vol.: 66 No.: 2