• International Area Studies Review
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• v.21 no.4
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• pp.159-172
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• 2017

In a typical trend-cycle decomposition of GDP, the trend component is usually assumed to follow a random walk process. This paper considers an ARIMA trend and assesses the validity of the ARIMA trend model. I construct univariate and bivariate unobserved-components(UC) models, allowing the ARIMA trend. Estimation results using U.S. data are favorable to the ARIMA trend models. I, also, compare the forecasting performance of the UC models. Dynamic pseudo-out-of-sample forecasting exercises are implemented with recursive estimations. I find that the bivariate model outperforms the univariate model, the smoothed estimates of trend and cycle components deliver smaller forecasting errors compared to the filtered estimates, and, most importantly, allowing for the ARIMA trend can lead to statistically significant gains in forecast accuracy, providing support for the ARIMA trend model. It is worthy of notice that trend shocks play the main source of the output fluctuation if the ARIMA trend is allowed in the UC model.

• Journal of the Korean Data and Information Science Society
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• v.22 no.5
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• pp.829-837
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• 2011

Since Harvey (1989), many approaches for applying unobserved components (UC) models to both univariate and multivariate time series analysis have been developed. However, practitioners still tend to use traditional methods such as exponential smoothing or ARIMA models for modeling and predicting time series data. It is well known that the UC model combines the flexibility of ARIMA models and the easy interpretability of exponential smoothing models by using unobserved components such as trend, cycle, season, and irregular components. This study reviews the UC model and compares its relative performances with those of the other models in modeling and predicting the real gross domestic products (GDP) in Korea. We conclude that the optimal model is the UC model on basis of root mean squared error.

• Korea journal of population studies
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• v.25 no.2
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• pp.5-40
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• 2002

Using detailed data of women's work history, this study analyses the transition process between employment and non-employment over the life history in order to identity individual and structural determinants in the processes. Korean women comprise very heterogeneous groups in terms of work continuity: one group having a continuous work history and another having an interrupted work experience. While 4.0% of total women have stayed in the labor market since leaving school, 17.3% have not worked outside at all and remaining 87.9% have experienced into and out of the labor market at least once. On the average, the cumulated time of employment per woman is 8.2 years and the cumulated time of unemployment is 13.1 years. Thus Korean women work a total of only 38.5% of their whole lifetime after leaving school. We can conclude that the increase of the employment rate of married women in Korea since the 1970s has been due to the increase of the new entrants with short or little working careers into the labor market, not to the increase of women's work continuity on the whole. A women's educational achievement does not seem to be positively related to employment duration, contrary to the suggestion of the human capital theory, Rather, family variables, especially the existence of the child under 6 yens old, is a more significant determining factor for an individual's exit from employment. And there is little difference among different age cohorts which implies little improvement in the employment continuity of younger women. This study also documents the importance of structural variables, such as the type of occupation, as significant determining factors for the hazard rate. Specially women with professional jobs tend to stay longer in the labor market. Therefore, women's entry into more professional occupations is expected to contribute to the continuity of employment. Our results also show that duration-dependence is not spurious. When unobserved heterogeneity is controlled, the negative relation between the rate from employment and the duration of employment does not disappear.

• 한국사회정책
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• v.23 no.1
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• pp.95-123
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• 2016

As Korean society grows rapidly older, a systematic analysis of the determinants of labor supply behavior among the elderly becomes a prerequisite for designing more effective senior employment policies and income security regime for the elderly. Literatures review shows that a majority of previous researches have been ignoring the problem of "endogenous predictor" especially when it comes to the estimation of the effects of the two key variables, education and non-labor income, on labor supply decisions among older people. They have failed to take into consideration the unobserved heterogeneities which might affect both labor supply decisions of the elderly and their levels of education and non-labor income, which means, according to some econometric literatures, that the estimated coefficients of the two predictors can be inconsistent. The paper tries to redress the endogeneity problem by employing a panel logit model with data from the 1st. to 4th. wave of the KLoSA(Korean Longitudinal Survey of Ageing) to estimate the effects of key predictors on the probability of getting jobs among older people(ages of 60 or older). Both a random effects and a fixed effects model reaffirms that non-labor income has a negative effect on the chances of being employed. And a random effects model shows that the effect of education is also negative, as has frequently been reported by previous studies. That means the effects of education and non-labor income on elderly employment remain negative after the effect of unobserved heterogeneities is controled for and the problem of endogenous predictors is redressed through an appropriate panel data analysis. These findings mean, in turn, that when Korean baby-boomers, who had acquired an unprecedentedly higher level of education and were expected to enjoy ever-larger amount of non-labor income than their preceding generations, retires in near future, their incentives to work will become much weaker and the lack of labor-force and the burden of financing increased public pension expenditure will become more troublesome. The paper concludes with recommending some policy initiatives helpful to solve these expected problems.

• The Korean Journal of Applied Statistics
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• v.29 no.4
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• pp.581-594
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• 2016

We introduce innovations state space exponential smoothing models (ISS-ESM) that can analyze time series with multiple seasonal patterns. Especially, in order to control complex structure existing in the multiple patterns, the model equations use a matrix consisting of seasonal updating parameters. It enables us to group the seasonal parameters according to their similarity. Because of the grouped parameters, we can accomplish the principle of parsimony. Further, the ISS-ESM can potentially accommodate any number of multiple seasonal patterns. The models are applied to predict electricity demand in Korea that is observed on hourly basis, and we compare their performance with that of the traditional exponential smoothing methods. It is observed that the ISS-ESM are superior to the traditional methods in terms of the prediction and the interpretability of seasonal patterns.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.1
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• pp.220-227
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• 2014

This paper introduces and applies the World Bank's methodology for constructing composite index or aggregating indicators. After recalculating the world competitiveness index of IMD using Unobserved Component Model(UCM) we compare it with the existing index and try to find some implications. We also try to construct the composite index for measuring the performance of local finance. We employ the Principal Component Analysis(PCA) for validating the appropriateness of selected indicators used in making the composite index. We found that the UCM and PCA are very useful and will be used widely in various evaluations such as regional development, local finance, local competitiveness and public enterprise, etc.

• Journal of Korean Society of Transportation
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• v.28 no.4
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• pp.119-128
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• 2010

Mode choice behavior is associated with travelers' latent behavior that is an unobservable preference to travel behavior or mode characteristics. This paper specifically addresses the problem of unobservable factors, that is latent behavior, in mode choice models. Consideration of latent behavior in mode choice models reduces the errors that come from unobservable factors. In this study, the authors defined the latent variables that mean a quantitative latent behavior factors, and developed the combined RP/SP model with latent variables using the mode choice behavior survey data. The data has traveler's revealed preference of existent modes along the Han River and stated preference of new water transit on the Han River. Also, The data has travelers' latent behavior. Latent variables were defined by factor analysis using the latent behaviour data. In conclusion, it is significant that the relationship between traveler's latent behavior and mode choice behavior. In addition, the goodness-of-fit of the mode choice models with latent variables are better than the model without latent variables.

• Economic Analysis
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• v.27 no.2
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• pp.1-40
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• 2021

Using an unobserved components model that features trend growth as a random walk, we find that GDP trend growth rates had gradually declined from the late 1980s to early 2010s in Korea. To uncover the underlying features of the slowdown, we use trend growth accounting. A major feature appears to be a significant decline in the growth rate of labor productivity. To be specific, the first gradual decline in trend growth, which started in 1988 and continued to 1998, is associated with a drop in TFP measured in labor-augmenting units. This finding is inconsistent with the hypothesis that the slowdown in GDP trend growth can be attributed to the 1997-1998 Korean financial crisis. Sluggish investment growth is behind the second period of the gradual slowdown, from 2002 to 2012.

• KDI Journal of Economic Policy
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• v.26 no.2
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• pp.3-62
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• 2004

This paper estimates Korea's natural rate of unemployment using various estimation methods such as pure time-series methods, reduced-form methods, and structural form methods, with discussion about relative advantages and disadvantages of each estimation method. This paper also provides the confidence interval of the estimated natural rate of unemployment by the Monte Carlo integration method. Though multivariate unobserved component model exhibits better performance in many aspects than other estimation methods, awareness should be raised for a potential misspecification problem of a multivariate unobserved component model. Considering that each method has its own advantages and disadvantages, it is recommended to make an inference on the natural rate of unemployment based on common results among various methods. Korea's natural rate of unemployment was estimated to be around 3.8~4.0% on average in the period of 1979:I~1987:IV, and to decline to 2.5~2.9% in the period of 1988:I~1997:IV. During the Asian crisis, it is estimated to peak at near 4.8% and to have been on a downward trend since then.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.2
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• pp.153-159
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• 2019

Job creation is the most important issue in the labor market these days, and the quality of jobs is also very important in order to resolve the mismatches that are taking place in the labor market. Kim Young-min (2014) developed the "2012 Quality of Employment Index" with twenty indicators in seven categories, including employment opportunities, to objectively assess the local labor market. This method presents the concept of the aggregate indicator, 'Quality of Work Index', and has the advantage of being easy to produce. However, it is difficult to statistically verify the adequacy of the constitutive indicators and, based on this, make them a single aggregate index through statistical techniques. Therefore, we developed an alternative '2012 Descent Work Index' and a confidence interval using Principal Component Analysis(PCA) and Unobserved Component Model(UCM) presented by Gi-Choon Kang & Myung-jig Kim (2014) and also calculated an alternative '2017 Descent Work Index' using the first half of 2017 local area labour force survey and compared its changes by region. The results of the empirical analysis show that the rank correlation coefficient between two methods of aggregating indicators, simple weight used in Young-min Kim's research, PCA method and UCM used in this study, were found to be statistically significant under 5% significance level. This implies that all methods are found to be useful. However, the PCA and UCM which determine scientific and objective weights based on data are preferred to Young-min Kim's approach. Since it provides us not only the level of aggregate indicator but also its confidence intervals, it is possible to compare ranking with the consideration of statistical significance. Therefore, it is expected that the method of constructing an aggregating indicator using UCM will be widely used in many areas in the future.