Verification of Recovery Process Under the Great Hanshin-Awaji Earthquake Disaster Based on the Recovery Index (Ri)

13th World Conference on Earthquake Engineering Vancouver, B.C., Canada August 1-6, 2004 Paper No. 1381

VERIFICATION OF RECOVERY PROCESS UNDER THE GREAT HANSHIN-AWAJI EARTHQUAKE DISASTER BASED ON THE RECOVERY INDEX (RI)

Yuka KARATANI1, Haruo HAYASHI2

SUMMARY

This paper provides Kobe citizen's life recovery process during the seven years after the Great Hanshin- Awaji Earthquake Disaster using RI (Recovery Index). In this research, there are two steps to clarify long- term life recovery process. First, RI database is created based on various kinds of official socioeconomic statistics of Kobe and Japan. Secondly, time phase during recovery process for seven years is examined using a cluster analysis based on RI database. Finally, it is clarified that there are three time phases in the recovery process, Jan.95 - Sep.95, Oct.95 - Sep.98, and Oct.98 - Jan.02, and the life recovery situation in each time phase is examined. As a result, it is found out that the recovery trend in the latest phase seems to stabilize.

INTRODUCTION

Remaining tasks in Hanshin-Awaji earthquake disaster recovery policy More than eight years have passed since the earthquake occurred. In less than two years until the end of the fiscal year 2004, that is, the end of Hanshin Awaji Earthquake Recovery Plan Period, we are required to achieve the remaining tasks, and to carry the mechanism created and extended during the earthquake recovery process forward to the mature society of the 21st century. In December 2002, the Administration of Hyogo Prefecture, the area affected by the disaster, formulated "Hanshin-Awaji Earthquake Recovery Plan Final Three-Year Promotion Program" as it faced with the last stage of the target period for the recovery [1]. This program defines and summarizes the basic concept and tasks for the remaining three years, the direction of measures for achieving the remaining tasks and the projects to be carried out mainly by the prefecture in three years. The important task, it points out, is to deliberate on the direction of measures that should be carried forward from the "recovery plan" to the "general plan". For example, in the Hyogo Prefecture "Latter Five-Year Promotion Program" [2], projects which had been considered as recovery measures have been narrowed down to be addressed as general measures (top priority measures: 288 projects, estimated project cost for three years: approx. 730 billion yen). Kobe city, aiming recovery in 10 years after the disaster, will also implement “Recovery Roundup and Verification (tentative title)” from this fiscal year on. In this program, the main subject, again, is to objectively grasp the recovery status of

1 Research Associate, Graduate School of Engineering, Kyoto University, Japan 2 Professor, Disaster Prevention Research Institute, Kyoto University, Japan the disaster-stricken area, to define the general idea of recovery measures, to narrow them down and to carry them on as general measures.

Viewpoints required for grasping the recovery status To analyze the recovery issues as we have discussed so far, we are required, first of all, to grasp the recovery status of the disaster-stricken area in multifaceted and objective manner. In “Kobe City Earthquake Disaster Recovery Roundup and Verification” [3], [4], which was implemented in 2000, "the Sector of Life Reconstruction", points out the necessity to define the concept of life reconstruction, and to proceed with verification, it discusses the specific theme: "what is life reconstruction?" in the first place. It explains the basic structure of life reconstruction during the recovery process in the following manner: "Life reconstruction" has a complex structure intertwining in with many other areas taken up in "Kobe City Earthquake Disaster Recovery Roundup and Verification". The basic structure is shown in Figure 1. The figure shows that the structure has recovery of infrastructure, the very basic issue in the process of recovery from the disaster, as the bottom layer, then reconstruction of individual houses and the city, revitalization of economy and measures to support medium and small-sized enterprises, all of which influence the reconstruction of the victims’ life. In addition, the victims’ life itself creates a specific problem associated with life reconstruction, which adds further complexity to the structure of "life reconstruction." The sector points out that, for this reason, it is difficult to define "life reconstruction" in short, and that it could not be easily grasped so far. It also makes it clear that seven factors of life reconstruction, i.e., "housing", "social network", "livelihood", "mind and body", "disaster preparedness", "government response", and "land use management" constitute the items to be verified regarding this difficult-to-define theme of “life reconstruction.” Accordingly, in grasping the life reconstruction status, it is considered important that we take a multifaceted approach.

Life rehabilitation of victims

Measures to Revitalization support medium Reconstruction City planning of economy and small-sized of houses enterprises

Recovery of infrastructure

Figure 1 Basic Structure of Life Reconstruction [3], [4] Source: Kobe City Earthquake Disaster Recovery Roundup and Verification: Sector of Life Reconstruction

Attempt of quantification with indices to indicate the life reconstruction status Karatani et al. (2000) [5] proposed the Recovery Index (RI) that can take the aspects as mentioned above into consideration, applying the concept of People's Life Indicators (PLI). And we tried to grasp the recovery process of Kobe city during the four years after the earthquake, using 120 types of socioeconomic statistics. As a result, the influence of the Hanshin-Awaji Earthquake Disaster in Kobe city could be roughly classified into 6 types of recovery and restoration status according to two factors: the size of drop immediately after the disaster and the extent of recovery afterwards. We also examined the recovery process in view of the nineteen items such as construction, transportation and export and import, included in the six recovery patterns. In examining the recovery status, however, there remain the following two questions: 1) By using RI, they only classified them into two groups: those that drop immediately after the earthquake, but return to the level before the earthquake (winner group), and those that did not return to the level before the earthquake (loser group). But what kind of situation do they regard as “recovery”? 2) In either group, the indices tend to stabilize with time whether it is a winner group or not (i.e., returning to the level before the earthquake or not). Is a similar stable trend still observed even when the latest data is added? Accordingly, in this paper, we used the RI database added with the latest data in the three years until January 2002 to verify the recovery process in Kobe city during the 7 years after the disaster. By clarifying the transition of recovery process patterns with time after the earthquake, we examine the concept of recovery as the tenth year of recovery after the disaster draws near.

OUTLINE OF METHOD TO ESTIMATE RECOVERY INDEX (RI)

Viewpoint for grasping the “life” Generally, published socioeconomic statistic values differ in unit or range of variation, so the correlation of indices cannot be compared easily. Accordingly, to standardize various indices, we adopted the concept of People's Life Indicators (PLI) proposed by the Social Policy Bureau of the Economic Planning Agency [6]. PLI was developed with a view to grasping the various aspects of people’s life in detail as well as the actual living conditions and characteristics of the local communities and to contributing to the improvement of the nation’s quality of life. The indices are used as a reference in discussing the question: “what is affluence in a real sense?” To be more precise, it classifies various socioeconomic statistics that show the nation’s living conditions are objectively and systematically into 8 areas of life activities: "dwelling", "spending", "working", "bringing up (children)", "healing", "playing", "learning", "socializing", and expresses them quantitatively by standardizing each index. We considered that this concept of PLI is similar to the seven factors of life reconstruction that were made clear in Kobe city in that they grasp the living conditions in a multifaceted and quantitative manner. Accordingly, in this paper, we employed the method proposed by PLI for standardizing respective socioeconomic statistics.

Calculation method of standardized index The standardized index is the value obtained by standardizing the rate of conversion so that the average of the absolute value of the rate of conversion in each month during the period of the survey equals 1, and by processing the rate of conversion of each month cumulatively, assuming the level of the reference month (here, December 1994) as 100. The method to standardize each index is as explained below. a) Calculation of centered rate of conversion Ci(t) Firstly, classify the method of calculation into two types based on the characteristics of respective indices Di(t), and calculate the centered rate of conversion Ci(t). The centered rate of conversion stands for the rate of conversion centered with regard to each index Di(t).

・CASE 1: when the index is an ordinary index or indicates the actual level itself

Di(t) − Di(t − 1) Ci(t) = ×100 Di(t) + Di(t − 1) [1-a] 2 where Di(t): each index, i: index number, t: time, Ci(t): centered rate of conversion.

・CASE 2: when the index is a ratio or 0 value or negative value

Ci(t) = Di(t)－Di(t－1) [1-b]

b) Calculation of standardization factor (Ai) N ∑ Ci(t) t=2 Ai = [2] N −1 where N: Number of time points during the standardization period. In this paper, the period of standardization is the period of 81 months from April 1992 to December 1998, hence N=81, Ai: standardization factor (weighted average of absolute value of rate of conversion). c) Calculation of standardized average rate of conversion (Bi(t))

Ci(t) Bi(t) = [3] Ai where Bi(t): standardized average rate of conversion (standardization of rate of conversion). d) Calculation of standardized index (Si(t)) Assuming Si(t) of the reference time point as 100 (%), calculate Si(t) with the following formula using the standardized average rate of conversion Bi(t)). In this paper, we set the reference time as December 1994, the previous month of the occurrence of the Great Hanshin Awaji Earthquake, hence Si (December 94) =100 (%).

・CASE 1:

200 + Bi(t) Si(t) = Si(t −1) ⋅ [4-a] 200 − Bi(t) ・CASE 2: Si(t) = Si(t −1) + Bi(t) [4-b] where Si (t): Standardization index Formula [4-a] can be regarded as a formula that matches the centeredrate of conversion of Si (t) with the standardized average rate of conversion Bi(t), and it can be rewritten as the following formula.

Si(t) − Si(t − 1) Bi(t) = ×100 Si(t) + Si(t − 1) [4-a'] 2

Definition of recovery index (RI) Figure 2 (a) and (b) show the conceptual model of recovery index (RI) proposed in this paper. Si1,x,t in Figure 2 (a), shows the actual variation of value of a certain socioeconomic index after the earthquake disaster in the area x. However, not all the change of actual values Si1,x,t after the earthquake may be attributed to the influence of the earthquake. For example, when the disaster hit the area x, suppose that the economy of the whole nation including the disaster-stricken area x suffered serious downturn due to other causes than the disaster. In such case, the actual value of a certain socioeconomic statistic of the area x may decrease due to two factors: the disaster and the stagnated economy. Therefore, in order to grasp the direct influence of the earthquake, it is necessary to assume the change that the indices would have shown when there was no disaster, and to eliminate the influence of social conditions caused by the factors other than the natural disaster that changed in the whole area including the area x. We assumed that the values certain socioeconomic indices of the area x might have shown if there was no earthquake would vary in the same manner as Si0,x,t, the values of socioeconomic indices of the same item in the area x0. That is to say, we assumed that the standardized index Si0,x,t of certain socioeconomic statistic in the area x0 would not be influenced by the disaster even in case it should occur, and would vary in the same manner as in the case of no disaster. And we assumed that socioeconomic statistic standardized index Si0,x,t, in the area x would vary in the same manner as that of area x0, the reference point. Therefore, the recovery index RI of the area x can be defined as the formula [5]. RIx,t=Si1,x,t−Si 0,x,t [5]

In this paper, we assume Si0,x,t as the value of the outside of the disaster-stricken area, that is, the value of the whole nation excluding the disaster-stricken area. As shown in Figure 2 (b) that shows the variation of recovery index RI, when the level of certain social indices in the area x is equal to that in the reference area x0, the recovery index RI becomes 0 and shows that the recovery in the area x has reached the level of the area x0. When the value is lower than the level of the reference area x0, then the influence of the disaster is shown in negative value, and when the value is higher than that level, the influence is shown in positive value. Based on such hypothesis, we clearly indicated the recovery and restoration status in view of the influence of the earthquake by continuously showing the difference between the level of each socioeconomic index of a certain area x and that of the reference area x0.

(a)

Si 0,x,t Standardized Index (%) Index 100

Si 1,x,t

Suffer

t 0 t ＋

(b) Index Rehabilitation t 0 0 t

RI x,t － Standard Month t 0

Figure 2 Conceptual model of RI

QUANTIFICATION OF RECOVERY PROCESS IN KOBE CITY AFTER HANSHIN AWAJI EARTHQUAKE DISASTER

Building a recovery index (RI) database Based on the method explained in the previous chapter, we estimated the variation of recovery process in Kobe city after the Hanshin Awaji Earthquake Disaster. The data used for individual index Di(t) are the socioeconomic statistics that have long been collected by Kobe City as part of its ordinary duties and were published in "Statistics Kobe" (April 1992 to April 1994) [7] and "Data Kobe" (October 1995 to January 2002) [8], [9]. This set of monthly data during the 118 months from April 1992 to January 2002 was provided to us by the courtesy of Kobe city. We obtained the national socioeconomic indices Si0,x,t, used for RI calculation from the Japanese Statistics monthly Report (Statistics Bureau, Management and Coordination Agency)" (April 1992 to July 2002) [10]. Out of all the data in these statistical reports, we used 120 items that allowed comparison between Kobe city and the whole nation during the target period. Please refer to Table 2 for details of these items. This database includes the financial indices of 10 cities and 10 towns in Hyogo Prefecture which are not the subject of this analysis. We built the database to grasp the recovery status in the disaster-stricken area, and we refer to it as "recovery index database".

Recovery patterns in view of RI We carry out a cluster analysis on 120 items of socioeconomic statistics during the period of 118 months from April 1992 to January 2002 in Kobe city, to classify and extract the recovery patterns that exist behind these data objectively and quantitatively. As to the cluster analysis method, we employed Ward method, one of the combination methods, for classification standard, and square Euclidean distance for measurement of distance of classification. In this paper, we used the above-mentioned methods for all the cluster analyses.

② 生活再建パターンの抽出Recovery pattern ②生活再建パターンの抽出Recovery pattern extraction (120（120 items)項目） extraction (120（120 items)項目）通企 . 通企新日公新月t. 有百貿. 就新. 日公e 新月t 有百貿 . 就 . e c e d 関業 y y 雇共c 設間uc 効e 貨 d 関t 業t 職 ay 規 y 雇共c 設間ru 効貨易n rt rt 職a 規o n s r m 易 n 輸r 倒r lo n s t m e 輸o 倒o 求l 就工a 住e 有st 求o 店額 e o o 率 lw 求 p就工a 住le 有s 求o 店額p p p 率ilw p s n l n c d p 出p 産p i 労 s 事in 宅a 効on 人c 売id x 出産x a 職m 労u 事i 宅a 効o 人n 売 i x m x a 職 m u F S C In A E Im E R E B F S C I A E I E R E B 1994-09 1994-09 1994-10 Phase I 1994-10 ① 1994-11 1994-11 時間 1994-12 1994-12 1995-01 通的公新月t. 有百貿. 企就新. 日 e c d 関業 y y 雇 1995-02 共c 設間ru 効e 貨易n t rt 職a 規o フ Phase II 工n 住s 有t 求m店 e 輸r 倒o 率w 求l 就 a le s o 額p 出o 産p il p s ェ事in 宅a 効on 人c 売id x p x a 職m 労u ー F S C In A E Im E R E B ズ 1994-09 の 2001-09 抽） 1994-10 月2001-10 1994-11 出が Phase III 2001-11 1994-12 2001-12 （118 1995-01 2002-01

Time phase extraction extraction phase Time months) (118 1995-02

2001-09

公新月t. 有百 . 通企就新. 日 e c 貿d 関業 y y 共c 設間ru 効e 貨易n t rt 職a 規o 雇 n s t m e 輸r 倒o w l 就工a 住le 有ns 求o 店額p o p 率il 求p s 事in 宅a 効o 人c 売id x 出p 産x a 職m 労u F S C In A E Im E R E B 1994-09 1994-10 1994-11 1994-12 1995-01 1995-02

2001-09 ）2001-10 月か2001-11 2001-12

（118 2002-01 (118 months) (118

(a) Cluster Analysis in terms of Time (b) Cluster Analysis in terms of Items Figure 3 Recovery Pattern Extraction Procedure To grasp the change of recovery pattern with time and the corresponding change of each item, we analyzed Table 1 Time Phases of Recovery them in the following two stages. Fig. 3 (a) and (b) 0 1992-04～1994-12 Ⅰ 1995-01～1995-09 show a mimetic diagram of the data set used for the Ⅱ 1995-10～1998-09 recovery process analysis; the horizontal axis of the Ⅲ 1998-10～2002-01 represents 120 items, and the vertical axis represents the target period (118 months). The procedure of 0 5 1 0 1 5 2 0 2 5 0 5 1 0 1 5 2 0 2 analysis is as follows. We first carry out a cluster 93.10 95.10 93.11 95.11 analysis in terms of time as shown in Fig. 3 (a), to 93.12 95.12 grasp how the recovery process evolved 93.08 96.10 93.09 96.11 with relevant time phases within the period of 118 93.06 P 96.04 months that covered before and after the earthquake, 93.07 h 96.05 93.05 a 96.06 and extract such time phases. Then, as shown in Fig. 93.04 s 96.07 3 (b), we extract the recovery pattern plotted in each 94.01 e 96.08 94.02 96.09 time phase extracted in Fig. 3 (a), and examine which 94.03 96.01 Ⅱ of the 120 items are included in each pattern. Finally, 94.08 96.02 P 94.09 96.03 we review the recovery status since the earthquake 94.12 97.01 h 94.10 97.02 disaster based on these results. a 94.11 96.12 s 94.06 97.12 e 94.07 99.04 a) Change of recovery process with time (extraction 94.05 99.06 of time phases) 94.04 99.05 0 92.04 99.03 Firstly, in order to extract the time phases that the 92.05 98.10 recovery process patterns with 120 items went 92.06 98.11 92.12 99.01 through during the period from April 1992 to January 93.02 99.02 93.03 98.12 2002, we carried out a cluster analysis in terms of 93.01 00.08 time (refer to Fig. 3 (a).) The values on the horizontal 92.08 00.09 92.09 00.10 axis in the figure represent similarity among the 92.10 00.12 samples. The smaller the value is, the greater the 92.11 00.04 92.07 P 00.05 similarity, and the larger the value, the less the 95.04 h 00.06 similarity. 95.05 a 00.07 95.03 s 00.01 Fig. 4 and Table 1 are the dendrogram and table P 95.08 00.02 I e which show the result of grouping the socioeconomic 95.09 Ⅲ 99.12 95.07 00.03 statistical data on 120 items in Kobe city by similarity 95.01 99.10 95.02 99.11 (distance). They suggest that the recovery process, 98.05 99.09 which includes 120 items, went through changes in 98.06 99.07 98.04 99.08 four phases. Phase 0 represents the period from April 97.04 01.12 1992 to December 1994, that is, from the beginning 97.05 02.01 P 97.03 01.10 of the statistical data until just before the occurrence h 97.07 01.11 of the Great Hanshin-Awaji Earthquake Disaster. As a 97.08 01.08 s 97.09 01.09 far as the indices of 120 items, i.e., the subject of this e 97.10 01.07 analysis, are concerned, the data shows that the 97.11 00.11 97.06 01.05 earthquake brought about a significant change that is Ⅱ 98.08 01.06 98.09 01.04 distinct from the previous pattern of change with 98.07 01.01 time. Phase I represents the period from January 1995 98.01 01.02 98.02 01.03 to September 1995, which corresponds to the period 98.03 of confusion immediately after the earthquake. In other words, the data shows that the period of direct Figure 4 Result of Cluster Analysis in confusion caused by the earthquake subsided in nine terms of Time months after the earthquake. Phase II represents the *94.12 indicates December, 1994 period from October 1995 to September 1998, which corresponds to the period of emergency three-year plan which aimed for the recovery of the city, life and the economy in the disaster-stricken area. In a sense, we can see that it suggests the completion of the first part of the recovery period. Phase III represents the period from October 1998 till the end of the analysis period. In a sense, it is considered as the latter part of the recovery period. In a way, we can say that we are still in this phase now. These are the distinctive features of the respective phases. We will now follow the recovery process of each phase and analyze the items included in these patterns. b) Changes in recovery pattern with time The time phases extracted in the previous section suggest that there are some changes in recovery pattern in each of phases. To clarify the changes in recovery pattern in each phase, we carried out a cluster analysis in terms of items. (Refer to Fig. 3 (b).). The result shows that there are respectively two types (period 0 to I), three types (period 0 to II), and six types (period 0 to III and 0 to December 98) of patterns in the recovery process in each time phase. To extract the potential trend in each pattern, we obtained the average variation of the socioeconomic indices which belong to the same group for each period. To be more precise, by averaging monthly data of all indices belonging to the same group, we tried to eliminate the influence of errors of the individual indices and find the real features of each group. Fig. 5 (a) to (c) show the two types, three types and six types of recovery patterns extracted from the 120 items of socioeconomic indices in the respective periods as mentioned above. When we examine the period of 0 to I shown in Fig. 5 (a), the 9-month period after the earthquake is classified into two groups depending on the size of drop in variables groups immediately after the earthquake. The period of 0 to II shown in Fig. 5 (b) could be classified into two groups: those in which the influence of the earthquake is recognized clearly (II-1, II-2) and those in which the influence is not recognized clearly (on the decrease) (II-3). The former can be further classified into two subgroups: those that showed a temporary drop due to the earthquake, but were returning to the level before the earthquake (II- 1), and those that failed to return to the level before the earthquake (II-2). The latter, on the other hand, already showed a slight decrease before the earthquake, sharply decreased for approx. three years after the earthquake, temporarily showed a sharp increase in May 1998, but again shows a declining trend as before. In the same manner as above, the period of 0 to III shown in Fig. 5 (c) can be roughly classified into two groups: those that clearly show the influence of the earthquake (III-1 to III-4) and those that do not show the influence clearly (III-5, III-6). III-5 of the latter group shows that the living standard in Kobe city was always above the national average both before and after the earthquake. III-6 shows a gradual decrease before the earthquake, decreased sharply for approx. three years after the earthquake, temporarily showed a sharp increase in May 1998, but again shows a declining trend as before. On the other hand, those items which clearly showed the influence of the earthquake showed a temporary drop due to the earthquake, but they are then classified into two types: those that showed temporary drop after the earthquake, but returned to the level before the earthquake (III-1, III-2) and those that did not return to the level before the earthquake (III-3, III-4). The latter group showed not only a temporary drop after the earthquake, but also a trend of gradual decrease which became notable after the earthquake; such trend was not visible before the earthquake. Accordingly, as the administration takes measures, the transition of socioeconomic indices included in this group should be continuously monitored even after the earthquake; these are considered as the items that will require careful attention. In addition to the classification by recovery status, the data could be classified into two groups, large and small according to the size of drop of variables that appeared immediately after the earthquake. The result suggests that III-1 and III-3 underwent smaller drop caused by the disaster when compared with III-2 and III-4, though they were apparently affected by the earthquake. （a）92.04～95.09 （ｂ）92.04～98.09 （ｃ）92.04～02.01

14 12 Ⅲ－5 10 (3) 8 6 4 2 0 -2 -4 -6 -8 -10 -12 -14 14 14 14 12 12 12 Ⅰ－1 Ⅱ－1 92-01 93-01 94-01 95-01 96-01 97-01 98-01 99-01 00-01 01-01 02-01 10 (91) 10 (88) 10 Ⅲ－1 (64) 8 8 8 6 6 6 4 4 4 2 2 2 0 0 0 -2 -2 -2 -4 -4 -4 -6 -6 -6 -8 -8 -8 -10 -10 -10 -12 0 Ⅰ -12 0 Ⅰ Ⅱ -12 0 Ⅰ Ⅱ Ⅲ -14 -14 -14 14 12 92-01 93-01 94-01 95-01 96-01 97-01 98-01 99-01 00-01 01-01 02-01 92-01 93-01 94-01 95-01 96-01 97-01 98-01 99-01 00-01 01-01 02-01 92-01 Ⅲ－93-01 394-01 95-01 96-01 97-01 98-01 99-01 00-01 01-01 02-01 10 (22) 8 【Impact : small】【stable】 6 4 2 0 -2 -4 -6 -8 -10 -12 Ⅱ－3 -14 14 12 92-019 Ⅲ93-01 9 －294-01 9 95-019 96-019 97-01 9 98-01 9 99-019 00-010 01-01 0 02-01 0 10 (16) 8 6 4 2 0 14 -2 12 Ⅱ－2 (27) -4 10 -6 8 -8 6 -10 4 -12 2 -14 0 12 -2 8 6 10 -4 92-01 Ⅲ－93-01 494-01 95-01 96-01 97-01 98-01 99-01 00-01 (13)01-01 02-01 8 Ⅰ－2 (29) -6 4 6 -8 2 4 -10 0 2 -12 -2 0 -14 -4 -2 -6 -4 -8 -6 92-01 93-01 94-01 95-01 96-01 97-01 98-01 99-01 00-01 01-01 02-01 -10 -8 -12 -10 【stable】 -14 -12 -16 -14 -18 -16 -20 6 5

4 92-01 93-01 94-01 95-01 96-01 97-01 98-01 99-01 00-01 01-01 02-01 92-01 93-01 94-01 95-01 96-01 97-01 98-01 99-01 00-01 01-01 02-01 2 (5) 0 0 -5 (2) 【Impact : large】 -2 -4 -10 -6 -8 -15 -10 -12 -20 -14 -25 -16 -18 -30 -20 Ⅱ－3 -22 -35 -40

92-01 93-01 94-0 1 95-0 1 96-01 97-01 98-0 1 99-0 1 00-01 01-01 02-0 1 -45 Ⅲ－6 【decrease gradually】 -50 92-01 93-01 94-01 95-01 96-01 97-01 98-01 99-01 00-01 01-01 02-01

Figure 5 Recovery Process of Each Time Phase

Recovery status by area viewed from the recovery pattern We examined here which indices constitute the recovery pattern in each time phase, or in other words, what sort of recovery and restoration process the various social activities in Kobe city went through. Table 2 (a) to (c) show the group of items that constitute the recovery patterns of each time phase shown in Fig. 5 (a) to (c). The vertical columns show the socioeconomic statistical item ID’s and their description used in this paper. The horizontal row show the extracted recovery pattern in each period, and it is marked gray where applicable. In Fig. 5, the number in the parentheses in the upper center right shows the number of index items included in each pattern. Let us examine the number of items that constitute the recovery pattern and the changes in content of each time phase. a) April 92 – September 95 (Phase 0 - I) Table 2 (a) shows that 91 items (76%), i.e., the majority of items, showed a relatively slight drop, while remaining 29 items (24%) showed a significant drop, during the period after the earthquake up to Phase I. Those items that showed the latter pattern are total population, population net increase, net migration, imports, and private railway companies (Hankyu, Hanshin, Sanyo, Kobe Express and Kobe New Transit). As to the port and railways, the earthquake caused serious damage to the infrastructure itself such as berths, station houses and rails. They were, therefore, obliged to suspend their services immediately after the earthquake, which caused a significant drop in the number of passengers. As to the items related to population, as many as 4,569 people died, and there were 236,899 refugees at peak time. Therefore, more people moved out to less damaged areas and less people moved in from outside of the city. [11]. b) April 92 – September 95 (Phase 0-II) Table 2 (b) shows that 88 items (73%), which underwent a slight drop immediately after the earthquake, soon returned to the level before the earthquake by Phase II, while remaining 27 items (23%) dropped significantly immediately after the earthquake, and still cannot return to the level before the earthquake afterwards. We also extracted a new pattern, which showed a slight decrease before the earthquake, decreased sharply for three years after the earthquake, and then temporarily showed a sharp increase in May 1998, but then turned to a declining trend as before. Those items which showed a small drop immediately after the earthquake in Phase I correspond to the indices groups that returned to the level before the earthquake in Phase II. And the items that showed a sharp drop immediately after the earthquake correspond to the indices groups that could not return to the level before the earthquake in Phase II. That is to say, the recovery status in Phase II is dependent on the size of drop immediately after the earthquake in Phase I. Items that showed the new pattern II-3 were: total population, population net increase, net migration, and number of people on public livelihood aid, and housing aid. Among these items, items related to population are considered to have been influenced by such factors as deaths, refugees, increase of people who moved out of the city, and decrease of people who moved into the city as explained previously. As to number of people on public livelihood aid and housing aid, the people who were already on public aid before the earthquake partly overlap the victims of the disaster. Therefore, the special measures implemented for the victims after the earthquake decreased the needs for public support those people on public aid used to have. This trend is outstanding in housing aid, as the administration implemented special measures for over 110,000 damaged housings in Kobe city. c) April 92 – January 02 (Phase 0-III) Table 2 (c) shows that 80 (67%) items returned to the level before the earthquake by phase III, regardless of the size of drop immediately after the earthquake, while 35 items (29%) did not. There are also two new patterns that do not clearly show the influence of the earthquake: the process III-5 indicating that the Table 2 Index System based on Recovery Process of Each Time Phase (a) 92.04-95.09 (b) 92.04-98.09 (c) 92.04-02.01 ID 指標項目 Ⅰ-1 Ⅰ-2 Ⅱ-1 Ⅱ-2 Ⅱ-3 Ⅲ-1 Ⅲ-2 Ⅲ-3 Ⅲ-4 Ⅲ-5 Ⅲ-6 F1 Population(1000) Total F2 Net Increase Natural increase F3 Net migration F4 Vital Statistics Live birth F5 Deaths F6 Marriages F7 Divorces F8 Department Sales Total(100mill.yen) F9 Finance Balance of deposits F10 (10mil. yen) Loans & discounts F11 Enterprice Cases F12 Bankruptcies Amount of liabilities F13 Foreign Trade Exports F14 (100mill. yen) Inports F15 Building Construction Floor area F16 Started （1000m2） Net housing units F17 Consumer Price Total F18 Indices Food F19 (100mill. yen) Living expenditure F20 New job applicants ratio F21 Sales of Large- Total F22 scale Retail Stores Clothing F23 Department stores Food & bevarages F24 (mill. yen) Furniture F25 Household electric appliances F26 Household equipment F27 Sales of Large- Total F28 scale Retail Stores Clothing F29 (Supermarkets) Food & bevarages F30 (mill. yen) Furniture F31 Household electric appliances F32 Household equipment F33 West JR Total(1000) F34 PrivateRailways Total(1000) F35 Hankyu Railway Total F36 (1000) Sannomiya F37 Rokko F38 Okamoto F39 Hanshin Railway Total F40 (1000) Motomachi F41 Sannomiya F42 Mikage F43 Sanyo Railway Total F44 (1000) Itayado F45 Tsukimiyama F46 Tarumi F47 Kobe Railway Total F48 (1000) Minatogawa F49 Suzurandai F50 Kita-suzurandai F51 Nishi-suzurandai F52 Kobe Rapid Railway Total F53 (1000) Sannomiya F54 Motomachi F55 Kosoku-Kobe F56 Shinkaichi F57 Kosoku-Nagata F58 Hokushin Railway Tanigami(1000) F59 Kobe Municipal Total F60 Subway Sannomiya F61 (1000) Minatogawa Park F62 Shinnagata F63 Myodani F64 Gakuentoshi F65 Seishin-chuo F66 Portliner Total F67 (1000) Sannomiya F68 Shiminbyoin F69 Shiminhiroba F70 Rokkoliner Total F71 (1000) Sumiyoshi F72 Uozaki F73 Islandcenter F74 Municipal Bus Total F75 Average of Total F76 Monthly Living Foods F77 Expenditure Housing F78 (All Housholds) House & land rent F79 (100mill.yen) Fuel,light&water charges F80 Furniture & household F81 Clothes & footwear F82 Medical care F83 Transportaion & Commun. F84 Education F85 Reading & recreation F86 Others F87 Average of Mouthly Income F88 Receipts & Expenditure F89 Disbursements Surplus F90 Building Construction Total F91 Started Wooden F92 Floor Area by Use Steel&reinforced concrete F93 (1000m2) Reinforced concrete F94 Steel frame F95 Employment New application F96 Referrals Monthly active applications F97 (General&part-time New job openings F98 workers) Monthly active job opening F99 Employment Placements F100 Referrals Active applications F101 (Day labourers) New applications F102 Total day labourers F103 Employment Claimants who got paid F104 insurance Recipients basic allowance F105 (General employees) Amount of benefits F106 Employment Insurance Recipients basic allowance F107 (Day labourers) Amount of benefits F108 Public Livelihood Persons F109 Aid Total of expenditure on aid F110 (mill. yen) Livelifood F111 Housing F112 Educational F113 Medical care F114 Crime Penalcoad crime cases F115 Known to the police F116 Felonious offences F117 Larceny offences F118 Traffic Accidents Cases F119 Persons killed F120 Persons injured living standard in Kobe city was always above the national level before and after the earthquake and the process III-6 showing similar trend to that of II-3 described above. Here, we will focus on two types in the transition from Phase II: ① those which show a recovery trend in Phase II, but does not seem to recover in Phase III (II-1→III-3·III-4), and ② those which shifted to the new pattern III-5. Items that show the trend ① are: divorces, bankrupt companies, exports, consumer price index (food), Kobe Electric Railway Co., Ltd., Municipal Subway, Municipal Bus, average expenditure (education), unemployment insurance (claimants accepted as eligible, actual number of recipients) and traffic accidents (number of accidents, number of persons injured). When we focus on an outstanding item, the number of bankrupt companies did not immediately increase thanks to the emergency financing measures taken immediately after the earthquake, but large scale bankruptcies of financial institutions due to the earthquake occurred in the summer of 1996, one and half years after the earthquake, which greatly affected the whole number of bankruptcies. In Phase III, even though the recession became serious, it was a general trend in Japan, and when we see Kobe city only, the situation of bankrupt companies shows a recovery trend. Items related to exports and railways are under similar conditions in that the infrastructure itself suffered serious damage and that they have competitors. While the functions of the Port of Kobe were suspended, other ports such as the Port of Yokohama and the Port of Tokyo substituted its export and import functions, and these substitution measures seem to be continuously taken even after its functions recovered. Railway companies are competing in the same area, so the lines which suspended their service for longer period seem to have difficulty in recovering afterwards. For example, West Japan Railway Company and Hankyu Railway restored earlier than other companies and resumed their service. It suggests that, in case of businesses with competitors, suspension of service leads to a decrease of their share. Items that show the trend of ② are: balance of deposits, loans and discounts, and active job applications. Firstly, both balance of deposits and loans & discounts in Kobe city maintain a high level compared with the national average. It is characteristic that this trend did not change substantially before and after the earthquake. The number of active job applications remains at a high level compared with the national average, reflecting the effectiveness of the positive measures taken for employment. As to the new job offers to new applicants ratio (F20), however, we have to note that an increase in active job offers may not necessarily mean that the types of job desired by applicants are offered, as we consider the fact that F20 is not much affected by the earthquake [12].

Recovery status in view of recovery index (RI) As we have discussed in Chapter 3, Section 2, in Phase III, three and half years after the earthquake disaster, the recovery patterns III-1 to III-4, which include 115 items (96%) among 120 items, show that the recovery status does not change much and is stable. When we compare (c) and (d) in Table 2, we can see the items that constitute each recovery pattern are almost identical. The term "stable" here means a situation which "shows a fixed trend and no change from a certain point". From such viewpoint, III-1 and III-2 have recovered to the level before the earthquake, and show a fixed trend, always staying close to zero (national average) since Phase III. III-3 and III-4 once recovered to the level before the earthquake, but then show a fixed trend of gradual decrease since Phase III. Both cases are considered to be in a "stable" status. Such situation in Kobe city may be likened to a "symptom fixation" stage. Western medicine has the concepts of "cure" and "symptom fixation". "Cure" literally means that the disease is completely healed, while "symptom fixation" refers to a situation where no significant short-term improvement can be expected if the current treatment is continued, but no significant aggravation is expected either if the treatment is interrupted [13]. When we review the recovery process in view of RI based on these concepts, Phase I is a period of critical condition where all the areas are severely affected by the earthquake. An intensive care (for example, Hyogo Prefecture Emergency Three-Year Plan) at this stage may spell the difference between life and death. Phase II is likened to a situation where the patient’s life was saved by the first aid, but the patient successively undergo various treatments for rehabilitation (recovery measures) to avoid after-effects in future. Phase III is the period of symptom fixation, in which symptoms have become stable, but long-term treatment is given with emphasis on specific points in order to alleviate the aftereffects that still remain here and there. According to this analogy, we should not regard the stability of RI values as an indication of stagnancy of the recovery process, but we should rather think that the recovery process is in progress, and that a long- term specific measures for the remaining specific issues are now required.

CONCLUSION AND OUR CHALLENGE IN FUTURE

In this paper, we verified the recovery process of Kobe city during the 7 years from the occurrence of the Hanshin-Awaji Earthquake Disaster until January 2002 using recovery indices (RI). The outcome of this study is summarized as follows. 1) To grasp the long-term recovery process since immediately after the earthquake using recovery indices (RI), we developed a recovery index (RI) database that contains 120 socioeconomic and financial indices of Kobe city and Japan. 2) To grasp transition of the recovery process during the 7 years from the earthquake, we carried out a cluster analysis in terms of time. As a result, we found that the recovery status went through 4 time phases as listed below. 0: April 1992 to December 1994 I: January 1995 to September 1995 II: October 1995 to September 1998 III: October 1998 to January 2002 3) To grasp what types of recovery patterns existed in each time phase obtained in 2), we carried out a cluster analysis in terms of items for each phase. As a result, we found that there are 2 types, 3 types and 6 types of recovery patterns in the periods 0 to I, the 0 to II, and 0 to III respectively. After sorting out the items that constitute each pattern, we examined the features of recovery pattern in each period. 4) We suggested the way to interpret the fluctuation of indices when we examine the recovery status using RI. We emphasized that the stability of RI values in Phase III should not be regarded as an indication of stagnancy of the recovery process but that we should rather think that the recovery process is in progress, and that a long-term specific measures for the remaining specific issues are now required.

However, the data used for the analysis of current recovery process represents the living conditions of Kobe citizens as a whole, and not of the victims alone. In this paper, we carried out an analysis on as many as 120 indices to examine various lives from many aspects. It is also necessary to use a small number of typical indices for the evaluation of the recovery measure programs. Accordingly, our challenge in future is to carefully examine the data to be used for an analysis, and to review what kind of data will enable us to grasp the "recovery of victims" more accurately.

REFERENCES

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