# A Comprehensive Estimation of the Economic Effects of Meteorological Services Based on the Input-Output Method

Authors: Xianhua Wu; Guo Wei; Lingjuan Yang; Ji Guo; Huaguo Lu; Yunfeng Chen; Jian Sun
Journal: The Scientific World Journal
 (2014)

---

## Abstract

Concentrating on consuming coefficient, partition coefficient, and Leontief inverse matrix, relevant concepts and algorithms are developed for estimating the impact of meteorological services including the associated (indirect, complete) economic effect. Subsequently, quantitative estimations are particularly obtained for the meteorological services in Jiangxi province by utilizing the input-output method. It is found that the economic effects are noticeably rescued by the preventive strategies developed from both the meteorological information and internal relevance (interdependency) in the industrial economic system. Another finding is that the ratio range of input in the complete economic effect on meteorological services is about 1 : 108.27–1 : 183.06, remarkably different from a previous estimation based on the Delphi method (1 : 30–1 : 51). Particularly, economic effects of meteorological services are higher for nontraditional users of manufacturing, wholesale and retail trades, services sector, tourism and culture, and art and lower for traditional users of agriculture, forestry, livestock, fishery, and construction industries.


---

## Body

## 1. Introduction

The production of sufficient food, fuel, and fiber to meet the world’s needs in a sustainable manner relies not only on the natural resources for growing them but also critically upon favorable weather conditions [1]. In recent years, frequent severe weather conditions such as droughts, flood, heavy snowfalls, and high temperatures have increasingly raised governmental and public concerns about meteorological services. However, to promote the utilization of valuable meteorological services, benefits need to be demonstrated quantitatively and answers to relevant questions need to be convincible. Critical questions include those regarding the economic effects, their measures, and estimation methods and models. For example, what are some quantitative results regarding the economic effects saved from disastrous weathers due to accurate meteorological service forecasts? What are some meaningful and reasonable measures for estimating such benefits of meteorological services? Unfortunately, there have been no effective methods and models established in the literature that can be employed by scientists for the desired estimation of the economic effects attributable to meteorological services. One difficulty is to correctly identify the economic effects saved from meteorological services as they are associated with each link of production or consumption. Another difficulty is to determine the costs operating the whole process of meteorological services that requires a wide range of considerations, including weather forecasting systems and assessment of many indirect costs. Still another difficulty is to describe a practical demand function—the demands of meteorological services can be highly implicit at present. Moreover, highly demanded assessment methods and models of economic effects benefited from meteorological services are also related to assessment policies, processes, and practice [2].Attempts in overcoming these difficulties were proposed by many researchers. Studies and exploratory trials have been carried out for exploring effective technologies and solutions both in China and abroad. These solutions can be roughly classified into three categories: direct field investigation, expert knowledge and qualitative analysis, and input-output assessment. Among the methods in the direct field investigation category, the focus is to measure the effects on the service objects that are rescued due to the use of meteorological services for users through the direct field investigation. Nguyen et al. calculated the economic effects of typhoon warning services in Vietnam [3]. By designing questionnaires based on the contingent valuation method, Birol et al. estimated the economic effect of water resources management [4]. Within the second category, expert knowledge and qualitative analysis, one calculates the effect brought by meteorological services using expert knowledge, Delphi method, or alike and then combining qualitative analysis measures and quantitative analysis results. Krieger and Green put forward the decision and optimization model of service effect estimation [5]. Recently, Xu estimated meteorological service effects using the Delphi method [6]. Integrating the experts’ knowledge into the epidemiology-based exposure-response functions, Kan and Chen assessed the health based economic cost of particulate air pollution in urban areas of Shanghai of China [7]. For the third category, input-output assessment, researchers compute the associated effects brought by services using an input-output method. Chen and Yin proposed a computing method of indirect and complete economic effects [8]. Using input occupancy output techniques, Wang established an accounting method for estimating the complete forward and backward economic effects for all industries in the national economy [9]. Hewings and Sonis proposed some concepts and algorithms relating to forward and backward linkage, correlative relations within industries, and output multipliers in input-output analysis [10]. Recently, Chen et al. estimated the associated social economic effects brought by oyster breeding in Taiwan [11], and Kerschner and Hubacek assessed the potential economic effects of peak oil using the input-output analysis [12]. These are just some of the existing researches achieved so far.The Delphi method (a structured communication technique, originally developed as a systematic, interactive forecasting method which relies on a panel of experts), is frequently employed by researchers. As a subjective, qualitative method, the Delphi method is essentially a feedback anonymous letter of inquiry method, with several advantages such as full role of experts, brainstorming, and high accuracy. However, it should be noticed that this expert opinion method can be utilized only when there is a lack of sufficient information—due to its drawbacks including(
1
) no clear criteria regarding expert selection, (
2
) lack of rigorous scientific analysis of the results, and (
3
) the final convergence of views having a tendency to follow the crowd.Moreover, except for a few case studies, most researchers only estimated the direct effects without investigating the indirect effects, which results in a gap in the literature of meteorological services. Moreover, most researchers simply combined field investigations and expert knowledge for estimating service effects in a single region, industry or enterprise; few studies utilized the input-output method to estimate the comprehensive service effects. Research, using input-output methods to calculate the associated and indirect economic effects, is rare. Chen and Yin and Wang, respectively, defined the concepts of indirect economic effect and complete economic effect and put forward corresponding algorithms [8, 9].Centered about consuming coefficients, partition coefficients and Leontief inverse matrix, we present in this paper the concepts of associated economic effect, indirect economic effect, and complete economic effect, input-output method, and algorithms that estimate, respectively, the associated, indirect, and complete economic effects. Generally, the direct economic effect is assumed to be known. In addition, illustrative examples are provided to explain the concepts and demonstrate the reliability and practicability of the models and algorithms regarding the theoretical innovation and economic effects for applications.Specifically, since the input-output table reflects more accurately the technical and economic relationships between industries in the national economy [13], it has become an ideal tool for calculating the associated and indirect economic effects of industries. According to the principle of doing certain things and refraining from doing other things, we present assessment models for associated, indirect, and complete economic effects based on the input-output table. Taking the meteorological service data in Jiangxi province in 2007 as an example, we obtained a series of results regarding the economic effects of meteorological services.Section2 describes the concepts, principles, and hypotheses. Section 3 introduces our estimation methods and algorithms. Section 4 illustrates our methods and algorithm with an actual example. The last section, Section 5, lays out the concluding remarks.


## 2. Concepts, Principles, and Hypotheses

In this section we will define concepts that describe economic effects and then introduce the principle of input-output table and several hypotheses.


### 2.1. Definition of Concepts

Here we assume that the direct meteorological service object is industryi.The direct economic effect of meteorological services is the increased economic effect due to the use of these meteorological services. To further explain this concept, assume that two similar industries, one utilizing the meteorological services and the other not, have similar input levels but with different outputs. The difference between the outputs that is beneficial from the use of the meteorological services is referred to as the direct economic effect.The associated economic effect of industryi is the economic effect due to the demands of other industries for the products (or services) produced (or provided) by industry i, which is to be calculated through the interdependency coefficients.The indirect economic effect of industryi is the sum of economic effects for industry i and other industries generated indirectly through an economic and technological relation.The complete economic effect of industryi is the increment of final output in all industries of national economy system brought by direct economic effect with the circulation of production-consumption.


### 2.2. Principle of the Input-Output Table

The input-output table describes resources of inputs and usages of outputs on all industries of the national economy in a matrix form for a period of time (usually one year). It reveals the quantitative relations which are not only interdependency but also mutually restraining for all industries of the national economy. As an important part of the national economic accounting system, the input-output table of China consists of three parts named as Quadrants I, II, and III. Table1 is illustrated.Table 1
Basic input-output table of China.
Output
Intermediate use
Final use
Inflow
Others
Total output
Input
Farming forestry, animal husbandry, and fishery
⋯
Public administration and social organization
Total intermediate use
Final consumption
Gross capital formation
Total
Total final use
Resident consumption
Government consumption
Total
Fixed capital formation
Increase in inventory
Total
Rural resident consumption
Urban resident consumption
Subtotal
Intermediate input
Farming forestry, animal husbandry, and fishery
⋮  Public administration and social organization
Quadrant I
Quadrant II
Total intermediate input
Increment
Laborers remunerationTaxes on production Depreciation of fixes assets Operating surplus Total increment
Quadrant III
Total inputInterconnected, these three parts of input-output table fully and systematically reflect the interrelations of all industries of the national economy, during the production cycle process from production to usage, by view of total quantity and structure of input-output. The following are some basic balance relationships in the input-output table:(i) line balance:(1)
Intermediate
use
+
Final
use
+
Others
=
Total
output
+
Inflow
,(ii) column balance:(2)
Intermediate
input
+
Increment
=
Total
input
,(iii) gross balance:(3)
Total
input
=
Total
output
Total
input
in
certain
industry
=
Total
output
in
this
industry
Total
intermediate
use
=
Total
Intermediate
input
,(iv) interdependency between industries.The interdependency between industries can be expressed as follows:(4)
x
i
=
∑
j
(
a
i
j
x
j
+
c
j
)
,
i
=
1,2
,
…
,
n
,
or in the matrix form X
=
A
X
+
C,  where x
i is the total output of industry i, c
i is the final demand of industry i, and a
i
j is the ratio of the input of industry i over the total demand of industry j
(
1
≤
i
,
j
≤
n
). Given n industries, a
i
j characterizes the distribution of inputs contributed by the n industries (i
=
1,2
,
…
,
n) to the total input required by industry j [15]. Matrix A will be called the technical coefficient matrix.


### 2.3. Hypotheses of Input-Output Model

The input-output model is a simplification of the Walrasian general equilibrium model [16]. There are three main hypotheses.H
1
: Pure industry: assume that each industry only produces one kind of product with one production technology. Meanwhile no different production technology can be selected or mutually replaced in the process of production across different industries.Models holdingH
1 can reflect the composition of material consumption and the relation between production and technology more accurately.H
2
: Each technical coefficient is relatively fixed. Regardless of factors of technical progress and increase of labor productivity, assume that each direct consumption coefficient (i.e., technical coefficient)a
i
j is fixed in a given period, that is to say, ignore influences of relevant dynamic factors.Here, dynamic factors include change of time, technology, price, industry, or product structure among others.  WithH
2, the analysis will be much simplified.H
3
: Linear relation: assume that there is a positive and proportional relationship between input and output in all industries of the national economy.H
3 is closely related to H
2. On the premise that direct consumption coefficient a
i
j is fixed, there must be a positive and proportional relationship between consumption and production, fixed consumption in production ignored.Despite exceeding the bounds of reasonable stipulations, these three hypotheses, presented in the forms subject to some ideal conditions, are fundamental in describing more general economic production relations and expanding the scope of input-output method, thus helpful for other researches as well.


## 2.1. Definition of Concepts

Here we assume that the direct meteorological service object is industryi.The direct economic effect of meteorological services is the increased economic effect due to the use of these meteorological services. To further explain this concept, assume that two similar industries, one utilizing the meteorological services and the other not, have similar input levels but with different outputs. The difference between the outputs that is beneficial from the use of the meteorological services is referred to as the direct economic effect.The associated economic effect of industryi is the economic effect due to the demands of other industries for the products (or services) produced (or provided) by industry i, which is to be calculated through the interdependency coefficients.The indirect economic effect of industryi is the sum of economic effects for industry i and other industries generated indirectly through an economic and technological relation.The complete economic effect of industryi is the increment of final output in all industries of national economy system brought by direct economic effect with the circulation of production-consumption.


## 2.2. Principle of the Input-Output Table

The input-output table describes resources of inputs and usages of outputs on all industries of the national economy in a matrix form for a period of time (usually one year). It reveals the quantitative relations which are not only interdependency but also mutually restraining for all industries of the national economy. As an important part of the national economic accounting system, the input-output table of China consists of three parts named as Quadrants I, II, and III. Table1 is illustrated.Table 1
Basic input-output table of China.
Output
Intermediate use
Final use
Inflow
Others
Total output
Input
Farming forestry, animal husbandry, and fishery
⋯
Public administration and social organization
Total intermediate use
Final consumption
Gross capital formation
Total
Total final use
Resident consumption
Government consumption
Total
Fixed capital formation
Increase in inventory
Total
Rural resident consumption
Urban resident consumption
Subtotal
Intermediate input
Farming forestry, animal husbandry, and fishery
⋮  Public administration and social organization
Quadrant I
Quadrant II
Total intermediate input
Increment
Laborers remunerationTaxes on production Depreciation of fixes assets Operating surplus Total increment
Quadrant III
Total inputInterconnected, these three parts of input-output table fully and systematically reflect the interrelations of all industries of the national economy, during the production cycle process from production to usage, by view of total quantity and structure of input-output. The following are some basic balance relationships in the input-output table:(i) line balance:(1)
Intermediate
use
+
Final
use
+
Others
=
Total
output
+
Inflow
,(ii) column balance:(2)
Intermediate
input
+
Increment
=
Total
input
,(iii) gross balance:(3)
Total
input
=
Total
output
Total
input
in
certain
industry
=
Total
output
in
this
industry
Total
intermediate
use
=
Total
Intermediate
input
,(iv) interdependency between industries.The interdependency between industries can be expressed as follows:(4)
x
i
=
∑
j
(
a
i
j
x
j
+
c
j
)
,
i
=
1,2
,
…
,
n
,
or in the matrix form X
=
A
X
+
C,  where x
i is the total output of industry i, c
i is the final demand of industry i, and a
i
j is the ratio of the input of industry i over the total demand of industry j
(
1
≤
i
,
j
≤
n
). Given n industries, a
i
j characterizes the distribution of inputs contributed by the n industries (i
=
1,2
,
…
,
n) to the total input required by industry j [15]. Matrix A will be called the technical coefficient matrix.


## 2.3. Hypotheses of Input-Output Model

The input-output model is a simplification of the Walrasian general equilibrium model [16]. There are three main hypotheses.H
1
: Pure industry: assume that each industry only produces one kind of product with one production technology. Meanwhile no different production technology can be selected or mutually replaced in the process of production across different industries.Models holdingH
1 can reflect the composition of material consumption and the relation between production and technology more accurately.H
2
: Each technical coefficient is relatively fixed. Regardless of factors of technical progress and increase of labor productivity, assume that each direct consumption coefficient (i.e., technical coefficient)a
i
j is fixed in a given period, that is to say, ignore influences of relevant dynamic factors.Here, dynamic factors include change of time, technology, price, industry, or product structure among others.  WithH
2, the analysis will be much simplified.H
3
: Linear relation: assume that there is a positive and proportional relationship between input and output in all industries of the national economy.H
3 is closely related to H
2. On the premise that direct consumption coefficient a
i
j is fixed, there must be a positive and proportional relationship between consumption and production, fixed consumption in production ignored.Despite exceeding the bounds of reasonable stipulations, these three hypotheses, presented in the forms subject to some ideal conditions, are fundamental in describing more general economic production relations and expanding the scope of input-output method, thus helpful for other researches as well.


## 3. Estimation Models of Associated, Indirect, and Complete Economic Effects

### 3.1. Estimation Models of Associated Economic Effects

(1) Direct Interdependency. The direct interdependency means the economic and technological relation between an industry and another industry which needs products or services from the former. It is usually measured by the direct distribution coefficient h
i
j
(
i
,
j
=
1,2
,
…
,
n
). h
i
j represents the proportion of the products or services directly used as intermediate products distributed from industry i to industry j in the total output. The formula calculating h
i
j is
(5)
h
i
j
=
x
i
j
X
i
,
(
i
=
1,2
,
…
,
n
,
j
=
1,2
,
…
,
n
)
,
where x
i
j denotes the products or services used as intermediate products distributed from industry i to the latter and X
i is the total output of industry i.Clearly, the higher the direct distribution coefficient of an industry to another, the greater the direct interdependency of the former industry for the latter industry, and the more obvious direct driving effect.(2) Complete Distribution Coefficient. The complete distribution coefficient d
i
j
(
i
,
j
=
1,2
,
…
,
n
) is the complete distribution of industry j provided per unit of value-added in industry i. It can be calculated on the basis of complete consumption coefficient. The matrix form formula calculating  d
i
j is given by
(6)
D
=
(
I
-
H
)
-
1
-
I
,
where I is the n by n identity matrix and H is the matrix of direct distribution coefficients, that is, H
=
(
h
i
j
).  (
I
-
H
)
-
1 describes the total accumulative distribution effect and it is similar to the Leontief  inverse matrix (
I
-
A
)
-
1.The bigger the complete distribution coefficient, the greater the motivational effect of complete supply, and the bigger the complete interdependency between industries. Complete distribution coefficients not only reflect the direct impact among industries but also reflect the indirect impact of every level, which is more comprehensive for analyzing relativity between industries.(3) Associated Economic Effect. The associated contribution is the added value created by the service effect of an industry for the production of intermediate input. According to the balance relation of the input-output table and the theory of industry interdependency, the associated contribution of industry i  for the national economy is
(7)
E
i
=
∑
d
i
j
Y
i
j
.Here,d
i
j is the complete distribution coefficient of industry i for products of industry j, Y
i
j is the direct economic effect of meteorological service for industry j due to industry i, and E
i in (7) is called the associated economic effect of meteorological service from industry i.


### 3.2. Estimation Model of Indirect Economic Effect

Recall, from Section2.1, that the indirect economic effect is the economic effect brought indirectly through an economic and technological relation. According to the input-output model in Table 1, we can get the total output of one industry as follows:
(8)
∑
j
=
1
n
X
i
j
+
Y
i
=
X
i
,
(
i
=
1,2
,
…
,
n
)
.Here,X
i
j is the intermediate consumption, representing the product value consumed in industry j which is provided by industry i, Y
i is the product value which is used as final use in industry i, and X
i is the total output of industry i. By adding the direct consumption coefficients a
i
j
=
x
i
j
/
X
j  into the model, (8) can be turned into
(9)
∑
j
=
1
n
a
i
j
X
j
+
Y
i
=
X
i
,
(
i
=
1,2
,
…
,
n
)
.
The matrix form of (9) is A
X
+
Y
=
X, where A is the technical coefficient matrix, and we have
(10)
X
=
(
1
-
A
)
-
1
Y
.
In the input-output table, service effects can be represented as the increase of final output, assuming that the final outputs of other industries are fixed. On the basis of the direct economic effect of a certain industry produced by services, we will explain the indirect effect as Δ
X brought by the direct economic effect of an industry. Accordingly, (10) changes into the incremental form:
(11)
Δ
X
=
(
I
-
A
)
-
1
Δ
Y
.
Here, Δ
X is the indirect effect of this industry brought by meteorological services, (
I
-
A
)
-
1 is the Leontief inverse matrix, and Δ
Y is the direct effect of this industry brought by services which is represented as the increase of final use.


### 3.3. Estimation Model of Complete Economic Effect

According to the previously established estimation model for the indirect economic effect, the increment of final use brought by the direct effect in the first round isΔ
X
=
(
I
-
A
)
-
1
Δ
Y.The increase of output in the first round will improve resident income, thus increasing resident consumption, which will further lead to the increase of output in the second round. The whole process repeats itself in circle. Of course, there are some hidden assumptions. First, the economic system has an enormous amount of idle productive capacity so that there will not be induced investment in the process of circulation. Second, with the increasing resident income, the marginal propensity to consume is constant. Third, consumption structure does not change as consumption scale changes.Assume thatα
=
(
α
1
,
α
2
,
…
,
α
n
) denotes the vector of resident income structure in each industry (α
i is the ratio of laborers’ remuneration in total output for industry i). Let c denote the marginal propensity to consume. Then c
α
·
(
I
-
A
)
-
1
Δ
Y represents the increment for consumption brought by service effect in the first round. Let w be the column vector of resident consumption structure coefficient in input-output table. Element w
i in w is the ratio of consumption of each industry in the total value of that column. So w
c
α
(
I
-
A
)
-
1
Δ
Y is the resident consumption increment produced by the increase of final use in the first round. (
I
-
A
)
-
1
w
c
α
(
I
-
A
)
-
1
Δ
Y is the output increment induced by the increase of final use in the initial state and first round, and so on. This production-consumption-production cycle will go on until the system reaches a new equilibrium. The foregoing is expressed by a mathematical equation as follows:
(12)
Δ
X
=
(
I
-
A
)
-
1
Δ
Y
+
(
I
-
A
)
-
1
w
c
α
(
I
-
A
)
-
1
Δ
Y
+
(
I
-
A
)
-
1
w
c
α
(
I
-
A
)
-
1
w
c
α
(
I
-
A
)
-
1
Δ
Y
+
⋯
Then we can get
(13)
Δ
X
=
(
I
-
A
)
-
1
[
I
-
w
c
α
(
I
-
A
)
-
1
]
-
1
Δ
Y
.


## 3.1. Estimation Models of Associated Economic Effects

(1) Direct Interdependency. The direct interdependency means the economic and technological relation between an industry and another industry which needs products or services from the former. It is usually measured by the direct distribution coefficient h
i
j
(
i
,
j
=
1,2
,
…
,
n
). h
i
j represents the proportion of the products or services directly used as intermediate products distributed from industry i to industry j in the total output. The formula calculating h
i
j is
(5)
h
i
j
=
x
i
j
X
i
,
(
i
=
1,2
,
…
,
n
,
j
=
1,2
,
…
,
n
)
,
where x
i
j denotes the products or services used as intermediate products distributed from industry i to the latter and X
i is the total output of industry i.Clearly, the higher the direct distribution coefficient of an industry to another, the greater the direct interdependency of the former industry for the latter industry, and the more obvious direct driving effect.(2) Complete Distribution Coefficient. The complete distribution coefficient d
i
j
(
i
,
j
=
1,2
,
…
,
n
) is the complete distribution of industry j provided per unit of value-added in industry i. It can be calculated on the basis of complete consumption coefficient. The matrix form formula calculating  d
i
j is given by
(6)
D
=
(
I
-
H
)
-
1
-
I
,
where I is the n by n identity matrix and H is the matrix of direct distribution coefficients, that is, H
=
(
h
i
j
).  (
I
-
H
)
-
1 describes the total accumulative distribution effect and it is similar to the Leontief  inverse matrix (
I
-
A
)
-
1.The bigger the complete distribution coefficient, the greater the motivational effect of complete supply, and the bigger the complete interdependency between industries. Complete distribution coefficients not only reflect the direct impact among industries but also reflect the indirect impact of every level, which is more comprehensive for analyzing relativity between industries.(3) Associated Economic Effect. The associated contribution is the added value created by the service effect of an industry for the production of intermediate input. According to the balance relation of the input-output table and the theory of industry interdependency, the associated contribution of industry i  for the national economy is
(7)
E
i
=
∑
d
i
j
Y
i
j
.Here,d
i
j is the complete distribution coefficient of industry i for products of industry j, Y
i
j is the direct economic effect of meteorological service for industry j due to industry i, and E
i in (7) is called the associated economic effect of meteorological service from industry i.


## 3.2. Estimation Model of Indirect Economic Effect

Recall, from Section2.1, that the indirect economic effect is the economic effect brought indirectly through an economic and technological relation. According to the input-output model in Table 1, we can get the total output of one industry as follows:
(8)
∑
j
=
1
n
X
i
j
+
Y
i
=
X
i
,
(
i
=
1,2
,
…
,
n
)
.Here,X
i
j is the intermediate consumption, representing the product value consumed in industry j which is provided by industry i, Y
i is the product value which is used as final use in industry i, and X
i is the total output of industry i. By adding the direct consumption coefficients a
i
j
=
x
i
j
/
X
j  into the model, (8) can be turned into
(9)
∑
j
=
1
n
a
i
j
X
j
+
Y
i
=
X
i
,
(
i
=
1,2
,
…
,
n
)
.
The matrix form of (9) is A
X
+
Y
=
X, where A is the technical coefficient matrix, and we have
(10)
X
=
(
1
-
A
)
-
1
Y
.
In the input-output table, service effects can be represented as the increase of final output, assuming that the final outputs of other industries are fixed. On the basis of the direct economic effect of a certain industry produced by services, we will explain the indirect effect as Δ
X brought by the direct economic effect of an industry. Accordingly, (10) changes into the incremental form:
(11)
Δ
X
=
(
I
-
A
)
-
1
Δ
Y
.
Here, Δ
X is the indirect effect of this industry brought by meteorological services, (
I
-
A
)
-
1 is the Leontief inverse matrix, and Δ
Y is the direct effect of this industry brought by services which is represented as the increase of final use.


## 3.3. Estimation Model of Complete Economic Effect

According to the previously established estimation model for the indirect economic effect, the increment of final use brought by the direct effect in the first round isΔ
X
=
(
I
-
A
)
-
1
Δ
Y.The increase of output in the first round will improve resident income, thus increasing resident consumption, which will further lead to the increase of output in the second round. The whole process repeats itself in circle. Of course, there are some hidden assumptions. First, the economic system has an enormous amount of idle productive capacity so that there will not be induced investment in the process of circulation. Second, with the increasing resident income, the marginal propensity to consume is constant. Third, consumption structure does not change as consumption scale changes.Assume thatα
=
(
α
1
,
α
2
,
…
,
α
n
) denotes the vector of resident income structure in each industry (α
i is the ratio of laborers’ remuneration in total output for industry i). Let c denote the marginal propensity to consume. Then c
α
·
(
I
-
A
)
-
1
Δ
Y represents the increment for consumption brought by service effect in the first round. Let w be the column vector of resident consumption structure coefficient in input-output table. Element w
i in w is the ratio of consumption of each industry in the total value of that column. So w
c
α
(
I
-
A
)
-
1
Δ
Y is the resident consumption increment produced by the increase of final use in the first round. (
I
-
A
)
-
1
w
c
α
(
I
-
A
)
-
1
Δ
Y is the output increment induced by the increase of final use in the initial state and first round, and so on. This production-consumption-production cycle will go on until the system reaches a new equilibrium. The foregoing is expressed by a mathematical equation as follows:
(12)
Δ
X
=
(
I
-
A
)
-
1
Δ
Y
+
(
I
-
A
)
-
1
w
c
α
(
I
-
A
)
-
1
Δ
Y
+
(
I
-
A
)
-
1
w
c
α
(
I
-
A
)
-
1
w
c
α
(
I
-
A
)
-
1
Δ
Y
+
⋯
Then we can get
(13)
Δ
X
=
(
I
-
A
)
-
1
[
I
-
w
c
α
(
I
-
A
)
-
1
]
-
1
Δ
Y
.


## 4. The Empirical Analysis of Meteorological Service Effects in Jiangxi Province

In this section, we will utilize the data obtained from Jiangxi province in 2007 to illustrate the concepts and models introduced in this paper (Section3). We employ the input-output method to estimate the economic effects of meteorological services based on the data given in the 2007 input-output table of Jiangxi [17].


### 4.1. Sample and Data

Zou et al. conducted a research on the evaluation reports of meteorological services in Jiangxi from 2003 to 2007 using the traditional expert investigation method (Delphi method) [14], while our purpose is, by utilizing the input-output model for the data supplied with the 2007 input-output table of Jiangxi, to estimate quantitatively the economic effects rescued from the preventive strategies that are established based on the meteorological information and the interdependency between industrial economic systems. Our setting of the study is different from that of Zou et al. as outlined below.(1) Data of Input-Output. They are from “Input-output table of Jiangxi in 2007” and “Input-output table of China in 2007,” where the latter was compiled by the Economic Accounting Department of the National Bureau of Statistics of China in 2007. The table involves 2 branch classifications; one is a table of 42 industries and, the other, a table of 135 industries. In this paper we use the data of 135 industries. According to the research of Gu et al., the resident marginal propensity to consume c in 2007 was 0.66 [18].(2) Data on the Direct Economic Effect of Meteorological Services. Using the expert investigation method, Zou et al. estimated the meteorological service effect on agriculture, forestry, husbandry, and fishery, transportation, construction, production, and supply of electric power, gas, and water, and insurance, manufacturing, resident service, and other services, wholesale and retail sale in Jiangxi province [14]. To correspond to the names of 135 industries in input-output table, we process the same data but utilizing our comprehensive economic effect estimation method as follows.(a)
Zou, Lu, and Dong synthesized agriculture, forestry, husbandry, and fishery into one industry. In this paper we split it equally into five shares with the same average proportions of 3.61%.
(b)
In Zou, Lu, and Dong’s study, there was only an average proportion of direct service effect for general “manufacturing”. In this paper we use 54 kinds of manufacturing in the table of 135 industries with the same proportions of 0.512%.
(c)
In Zou, Lu, and Dong’s study, there was only an average proportion of “insurance.” Considering that “insurance” is a subkey of “finance” in the table of 135 industries, we equate “insurance” with “finance,” whose ratio of meteorological service effect in total output is 1.943%.
(d)
In Zou, Lu, and Dong’s study, there was only an average proportion of “transportation and warehousing.” In this paper we treat 8 subkeys of “transportation and warehousing” in the table of 135 industries whose proportions are all 2.454% equally.
(e)
In Zou, Lu, and Dong’s study, there was only a contribution rate of “resident service and other services.” According to the table of 135 industries, “resident service and other services” will be subdivided into “resident service” and “other services,” whose proportions are all 0.484%.Specific results are provided in Table2.Table 2
Contribution rate of weather service in highly sensitive industries in Jiangxi province, China (Measuring unit: %).
Industry
Direct service effect in 2003–2007
Contribution rate of meteorological service effect
Agriculture
4.07–3.15
3.61
Forestry
4.07–3.15
3.61
Animal husbandry
4.07–3.15
3.61
Fishery
4.07–3.15
3.61
Agriculture, forestry, husbandry, and fishery
4.07–3.15
3.61
Convenience food manufacturing
0.631–0.392
0.512
Milk and dairy manufacturing
0.631–0.392
0.512
Condiments and fermentation products manufacturing
0.631–0.392
0.512
Other food manufacturing
0.631–0.392
0.512
Alcohol and wine manufacturing
0.631–0.392
0.512
Textile product manufacturing
0.631–0.392
0.512
Knitwear, weaving, and its product manufacturing
0.631–0.392
0.512
Textile wearing apparel, footware, and cap manufacturing
0.631–0.392
0.512
Furniture manufacturing
0.631–0.392
0.512
Sport, cultural, and educational supply manufacturing
0.631–0.392
0.512
Basic chemical raw material manufacturing
0.631–0.392
0.512
Fertilizer manufacturing
0.631–0.392
0.512
Pesticide manufacturing
0.631–0.392
0.512
Coating, printing ink, paint, and similar product manufacturing
0.631–0.392
0.512
Synthetic material manufacturing
0.631–0.392
0.512
Special chemical product manufacturing
0.631–0.392
0.512
Daily chemical product manufacturing
0.631–0.392
0.512
Pharmaceutical manufacturing
0.631–0.392
0.512
Chemical fiber manufacturing
0.631–0.392
0.512
Cement, lime, and gypsum manufacturing
0.631–0.392
0.512
Cement and gypsum product manufacturing
0.631–0.392
0.512
Brick, stone, and other building material manufacturing
0.631–0.392
0.512
Glass and glassware manufacturing
0.631–0.392
0.512
Ceramic product manufacturing
0.631–0.392
0.512
Refractory product manufacturing
0.631–0.392
0.512
Graphite and other nonmetallic mineral product manufacturing
0.631–0.392
0.512
Nonferrous metal and alloy manufacturing
0.631–0.392
0.512
Boiler and prime mover manufacturing
0.631–0.392
0.512
Metalworking machinery manufacturing
0.631–0.392
0.512
Hoist-transportation machine manufacturing
0.631–0.392
0.512
Pumps, valves, compressors, and similar machinery manufacturing
0.631–0.392
0.512
Other common equipment manufacturing
0.631–0.392
0.512
Mining, metallurgy, and building equipment manufacturing
0.631–0.392
0.512
Chemical, wood, and nonmetal processing equipment manufacturing
0.631–0.392
0.512
Special machinery for agriculture, forestry, husbandry, and fishery manufacturing
0.631–0.392
0.512
Other specialized equipment manufacturing
0.631–0.392
0.512
Railway transport equipment manufacturing
0.631–0.392
0.512
Automobile manufacturing
0.631–0.392
0.512
Vessel and floating facility manufacturing
0.631–0.392
0.512
Other transportation equipment manufacturing
0.631–0.392
0.512
Motor manufacturing
0.631–0.392
0.512
Transmission and distribution and control equipment manufacturing
0.631–0.392
0.512
Wire, cable, fiber optic cable, and electrical equipment manufacturing
0.631–0.392
0.512
Household electric and nonelectric appliance manufacturing
0.631–0.392
0.512
Other electrical machinery and equipment manufacturing
0.631–0.392
0.512
Communication equipment manufacturing
0.631–0.392
0.512
Radar and radio equipment manufacturing
0.631–0.392
0.512
Electronic computer manufacturing
0.631–0.392
0.512
Electronic component manufacturing
0.631–0.392
0.512
Home audio-visual equipment manufacturing
0.631–0.392
0.512
Other electronic equipment manufacturing
0.631–0.392
0.512
Instrument manufacturing
0.631–0.392
0.512
Cultural and office machinery manufacturing
0.631–0.392
0.512
Craft and other product manufacturing
0.631–0.392
0.512
Production and supply of power and heat
2.323–1.569
1.946
Production and supply of gas
2.323–1.569
1.946
Production and supply of water
2.323–1.569
1.946
Construction
2.513–1.769
2.141
Railway transportation
2.993–1.914
2.454
Road transportation
2.993–1.914
2.454
City's public transportation
2.993–1.914
2.454
Water transportation
2.993–1.914
2.454
Air transportation
2.993–1.914
2.454
Pipeline transportation
2.993–1.914
2.454
Handling and other transport service
2.993–1.914
2.454
Warehousing
2.993–1.914
2.454
Wholesale and retail sale
0.44–0.15
0.295
Insurance
2.279–1.607
1.943
Resident service
0.655–0.312
0.484
Other service
0.655–0.312
0.484
Data source: Zou et al. [14].It should be pointed out that the Delphi method is a structured communication technique, originally developed as a systematic, interactive forecasting method which relies on a panel of experts and thus subject to and dependent on the knowledge of the participating experts. Hence, this method is more subjective in nature.Moreover, since the available meteorological service data sets for Jiangxi province from 2003 to 2007 are quite rich, the input-output method would be more appropriate. In fact, the Delphi (expert opinion) method is utilized only when there is a lack of sufficient information (due to its three drawbacks stated in Section1).In contrast, our estimation model (input-output method) for obtaining quantitative results regarding the comprehensive economic effects of meteorological services is established on the inhesion relevance among different industries, which is more objective and provides a practical setting for preventive strategies and other recommendations to rescue in the face of extreme weather conditions.Specifically, since the input-output table reflects more accurately the technical and economic relationships between industries in the national economy [13], it has become an ideal tool for calculating the associated and indirect economic effects of industries. According to the principle of doing certain things and refraining from doing other things, we present assessment models for associated, indirect, and complete economic effects based on the input-output table. Taking the meteorological service data in Jiangxi province in 2007 as an example, we obtained a series of results regarding the economic effects of meteorological services.


### 4.2. Results and Analysis

By utilizing the estimation equations of associated economic effect (7), indirect economic effect (11), and complete economic effect (13), we summarize the results in Table 3.Table 3
Results of economic effects (measuring unit: ten thousand RMB).
Industry
Direct service effect
Associated economic effect
Indirect economic effect
Complete economic effect
Agriculture
224274.860
32254.572
307400.052
415246.092
Forestry
45652.060
67369.404
68169.407
80815.325
Animal husbandry
157244.380
13094.821
180582.946
245308.922
Fishery
65774.200
2730.388
69725.861
80974.323
Service of agriculture, forestry, husbandry, and fishery
22176.230
36522.675
31415.316
34289.819
Coal mining and washing
/
29468.833
64986.176
106900.696
Oil and gas exploration
/
2002.814
59147.069
96862.943
Ferrous metal ore mining
/
3.147
15374.575
17790.070
Nonferrous metal mining
/
6192.810
27888.475
35079.747
Other nonmetal ore mining
/
180479.691
27467.146
31787.500
Grain grinding
/
40438.204
8231.043
22338.272
Feed processing
/
76422.147
29632.467
39312.748
Vegetable oil processing
/
7223.678
3069.876
11041.238
Sugar industry
/
354.072
11.208
86.284
Slaughtering and meat processing
/
4688.495
3631.551
16511.096
Aquatic product processing
/
886.262
1136.525
6718.374
Other food processing
/
603.799
1374.011
16120.633
Convenience food manufacturing
1294.285
188.289
1363.028
7520.514
Milk and dairy manufacturing
541.542
175.256
716.447
4223.064
Condiments and fermentation products manufacturing
1733.750
595.822
2805.411
5249.706
Other food manufacturing
4296.243
129.679
4683.159
25718.227
Alcohol and wine manufacturing
3949.839
742.590
6565.676
20779.630
Soft drink and refined tea processing
/
368.611
729.371
3786.235
Tobacco processing
/
90.931
205.572
14109.853
Cotton, chemical fiber textile and printing, and dyeing finishing
/
2263.104
11392.778
36670.132
Weaving, dyeing, and finishing
/
424.478
308.375
5435.661
Linen textile, silk spinning, and finishing
/
1519.773
2792.121
7674.866
Textile product manufacturing
2318.879
11662.786
7111.676
12948.707
Knitwear, weaving, and its product manufacturing
3286.149
1361.131
4670.416
7287.079
Textile wearing apparel, footware, and cap manufacturing
7537.976
18570.466
19011.769
43126.773
Leather, fur, feathers (fine hair), and its product manufacturing
/
1591.953
9140.069
30904.725
Timber, wood, bamboo, rattan, palm, and straw processing
/
51003.512
23097.462
38102.199
Furniture manufacturing
7927.270
13202.959
11774.138
20665.662
Paper and paper product manufacturing
/
3417.195
20861.898
45138.795
Printing and copying for recording medium
/
2752.207
4972.889
17553.695
Sport, cultural, and educational supply manufacturing
5552.497
12173.136
14409.494
22219.404
Oil and nuclear fuel processing
/
53732.201
45330.912
74672.808
Coking
/
134.923
30533.565
35546.660
Basic chemical raw material manufacturing
4313.508
7067.420
27771.611
37444.661
Fertilizer manufacturing
4776.596
113030.519
46324.485
60428.552
Pesticide manufacturing
3479.818
123788.558
30955.208
40371.197
Coating, printing ink, paint, and similar product manufacturing
2246.195
73507.519
12012.993
16516.688
Synthetic material manufacturing
4390.088
8384.865
20399.731
28660.573
Special chemical product manufacturing
5617.388
5959.214
32088.072
44742.483
Daily chemical product manufacturing
5380.403
3648.736
8484.226
20895.037
Pharmaceutical manufacturing
14668.068
4186.108
22027.422
29524.215
Chemical fiber manufacturing
5324.564
9295.692
13389.803
19345.855
Rubber product manufacturing
/
36257.879
16756.519
26013.082
Plastic product manufacturing
/
67906.036
19624.883
38499.650
Cement, lime, and gypsum manufacturing
8157.829
185923.581
40322.398
49618.238
Cement and gypsum product manufacturing
1465.631
230146.363
7133.046
7690.405
Brick, stone, and other building material manufacturing
934.492
144240.892
4230.565
7271.283
Glass and glassware manufacturing
3514.849
36133.173
16109.635
22741.921
Ceramic product manufacturing
1071.437
116648.089
3055.160
4717.192
Refractory product manufacturing
23.347
32815.366
108.039
121.212
Graphite and other nonmetallic mineral product manufacturing
1815.357
23832.294
5177.474
6063.783
Ironmaking
/
123.489
2086.748
2427.965
Steelmaking
/
92.345
9490.169
11074.714
Steel rolling processing
/
253850.953
192794.942
223013.850
Ferroalloy smelting
/
915.104
8348.284
9723.447
Nonferrous metal and alloy manufacturing
15380.644
8219.925
59352.409
72456.541
Nonferrous metal rolling process
/
16988.377
35441.068
45998.841
Metal product manufacturing
/
46209.909
18022.247
31824.760
Boiler and prime mover manufacturing
1585.843
15390.963
5216.272
6956.593
Metalworking machinery manufacturing
1317.524
8476.230
4777.305
6708.909
Hoist-transportation machine manufacturing
751.089
560.301
1799.648
2400.930
Pumps, valves, compressors, and similar machinery manufacturing
747.080
18494.049
3112.927
4196.952
Other common equipment manufacturing
2549.709
33004.312
15292.951
19117.583
Mining, metallurgy, and building equipment manufacturing
1225.585
34734.644
5878.842
7334.650
Chemical, wood, and nonmetal processing equipment manufacturing
153.743
1372.453
594.162
828.217
Special machinery for agriculture, forestry, husbandry, and fishery manufacturing
542.986
86045.197
5151.476
6327.882
Other specialized equipment manufacturing
10897.859
7327.467
47018.932
66889.403
Railway transport equipment manufacturing
186.199
18862.441
3037.940
4247.180
Automobile manufacturing
6337.792
31957.175
31643.484
46873.349
Vessel and floating facility manufacturing
2552.346
5227.158
4394.514
5606.492
Other transportation equipment manufacturing
2430.771
535.248
2891.412
6278.044
Motor manufacturing
2773.806
27926.379
13458.015
17086.261
Transmission, distribution, and control equipment manufacturing
1124.588
54310.877
6471.885
8334.190
Wire, cable, fiber optic cable, and electrical equipment manufacturing
4094.003
114155.168
16208.657
21175.912
Household electric and nonelectric appliance manufacturing
4924.380
23225.400
7882.982
17166.417
Other electrical machinery and equipment manufacturing
10017.357
14318.681
21735.315
27076.277
Communication equipment manufacturing
2352.241
2951.962
4628.916
10437.479
Radar and radio equipment manufacturing
181.233
1602.207
281.370
326.689
Electronic computer manufacturing
1193.221
17732.838
4494.400
9978.567
Electronic component manufacturing
5151.759
6807.819
17136.031
27029.060
Home audio-visual equipment manufacturing
3591.788
1461.821
4379.862
20785.160
Other electronic equipment manufacturing
871.793
6197.221
1338.956
1758.516
Instrument manufacturing
3068.764
9233.189
12540.223
17682.669
Cultural and office machinery manufacturing
603.192
48454.565
2153.542
3659.179
Craft and other product manufacturing
3195.546
66736.291
11051.372
16906.321
Scrap waste
/
236.007
330.902
416.647
Production and supply of power and heat
86655.828
26555.778
232416.262
384403.028
Production and supply of gas
830.203
2633.266
1794.680
3742.844
Production and supply of water
7733.696
37911.991
12831.484
21718.429
Construction
384517.177
783.857
398017.605
411185.018
Railway transportation
44262.798
34882.827
139320.673
198323.547
Road transportation
100498.662
54551.412
180734.309
225390.320
City's public transportation
8640.534
20198.200
12884.220
16904.497
Water transportation
2287.128
14447.927
4474.668
7291.585
Air transportation
3791.430
19799.388
7387.494
11854.599
Pipeline transportation
/
0.000
0.000
0.000
Handling and other transport service
1992.648
10219.544
3805.300
5947.536
Warehousing
2736.210
9417.221
3598.809
4164.856
The postal service
/
22052.628
2228.910
4591.521
Telecommunication and information transmission service
/
12765.332
12776.421
39300.447
Computer service
/
2211.991
1412.032
2692.011
Software
/
517.298
70.752
184.895
Wholesale and retail sale
28363.365
33103.282
171367.334
286838.534
Accommodation
/
20236.829
7528.296
16449.092
Catering
/
22786.509
25574.979
49250.285
Banking, security, and other financial activity
/
33651.299
46885.264
82681.399
Insurance
/
38477.101
5864.920
11096.667
Real estate
/
6902.654
18166.860
78204.631
Leasing
/
118605.765
835.384
2422.092
Business service
/
15666.721
6283.722
10785.177
Tourism
/
74.551
128.804
3505.748
Research and experimental development
/
117186.760
1598.279
1857.017
Professional and technical service
/
136052.891
4321.458
5614.004
Science and technology exchange and promotion service
/
20825.614
803.687
1126.383
Geological exploration
/
0.000
0.000
0.000
Water management
/
115937.570
2979.632
4471.497
Environmental management
/
9469.365
1190.529
2282.958
Public facilities management
/
523.006
110.174
1655.620
Resident service
2045.384
13369.132
5267.168
13544.352
Other service
3366.220
26964.684
20683.657
33635.381
Education
/
2670.063
8415.407
33121.785
Health
/
3211.955
15980.637
33957.909
Social security
/
7518.737
82.898
106.042
Social welfare
/
4109.687
92.954
114.111
Press and publication
/
30820.604
2182.198
4817.494
Radio, television, film, and motion picture
/
158.709
148.309
1230.560
Culture and art
/
23.727
0.957
553.198
Sport
/
0.000
0.000
109.717
Entertainment
/
18301.346
4832.876
8490.062
Public management and social organization
/
3246.067
5919.578
7626.480
Total
1388263.853
3952190.571
3399128.942
5010533.474An analysis of Table3 reaches the following conclusions.(1) Due to the technical and economic relations between industries, the direct economic effect of services can bring to all industries the associated, indirect, and complete economic effects. The direct economic effect of meteorological service in Jiangxi province in 2007 was 13882.63853 million RMB, which brought the associated economic effect of 39521.90571 RMB, indirect economic effect of 33991.28942 RMB, and complete economic effect of 50105.33474 RMB. Three economic effects, respectively, increased by 1.847-fold, 1.448-fold, and 2.609-fold.The ratio range of input in associated economic effect in Jiangxi province is about 1 : 85.41–1 : 145.197, the ratio range of input in indirect economic effect is about 1 : 73.44–1 : 124.848, and the ratio range of input in complete economic effect is about 1 : 108.27–1 : 183.059, which are remarkably different from a previous estimation based on the Delphi method (stated below).Ren studied the “Input-output table of China in 2007” for the whole country using the traditional Delphi method and concluded that the effect ratio range of input in output brought by meteorological services in China is 1:30–1:51 [19].In contrast, our results suggest that the associated, indirect and complete economic effects brought by meteorological services are so huge that more attention should be paid to this field.(2) As observed from the calculation of associated economic effect brought by direct economic effect, the top five industries, in order of decreasing proportions of associated effect are refractory product manufacturing (1405.538-fold), special machinery for agriculture, forestry, husbandry, and fishery manufacturing (158.467-fold), cement and gypsum product manufacturing (157.029-fold), brick, stone, and other building material manufacturing (154.352-fold), and ceramic product manufacturing (108.871-fold). The bottom five are construction (0.002-fold), other food manufacturing (0.030-fold), fishery (0.042-fold), animal husbandry (0.083-fold), and agriculture (0.144-fold).Also, from the calculation of indirect economic effect brought by direct economic effect, the top 5 industries in order of decreasing increments are railway transport equipment manufacturing (15.316-fold), fertilizer manufacturing (8.698-fold), special machinery for agriculture, forestry, husbandry, and fishery manufacturing (8.487-fold), pesticide manufacturing (7.896-fold), and basic chemical raw material manufacturing (5.438-fold). The bottom five construction (0.035-fold), convenience food manufacturing (0.053-fold), fishery (0.060-fold), other food manufacturing (0.090-fold), and animal husbandry (0.148-fold).Furthermore, as observed from the calculation of complete economic effect brought by direct economic effect, the top 5 industries in order of decreasing increments are railway transport equipment manufacturing (21.810-fold), fertilizer manufacturing (12.1651-fold), special machinery for agriculture, forestry, husbandry, and fishery manufacturing (10.654-fold), pesticide manufacturing (10.602-fold), and wholesale and retail sale (9.113-fold). The bottom five are construction (0.069), fishery (0.231), warehousing (0.522-fold), service of agriculture, forestry, husbandry, and fishery (0.546-fold), and animal husbandry (0.560-fold).Thus, increments of indirect and complete economic effects on traditional meteorological service objects such as construction, agriculture, forestry, husbandry, fishery, and warehousing are comparatively low, while some industries such as railway transport, equipment manufacturing, and fertilizer manufacturing can reach more indirect and complete economic effects. Consequently, in the future, meteorological service should tilt toward industries including railway transport, equipment manufacturing, and special machinery for agriculture, forestry, husbandry, and fishery manufacturing and provide more targeted fine services to improve their indirect and complete economic effects of meteorological service.(3) As seen from the calculation of complete economic effect brought by indirect economic effect, the top five industries in order of decreasing increments are culture and art (577.222-fold), tobacco processing (67.673-fold), tourism (26.218-fold), weaving, dyeing, and finishing (16.627-fold), and public facilities management (14.027-fold). The bottom six are construction (0.033-fold), cement and gypsum product manufacturing (0.078-fold), service of agriculture, forestry, husbandry, and fishery (0.092-fold), refractory product manufacturing (0.122-fold), steel rolling processing (0.157-fold), and ferrous metal ore mining (0.157-fold). It indicates that owing to the production-consumption-production cyclic effect, the output multipliers of industries like culture and art, tobacco processing, and tourism are bigger than those of construction, agriculture, forestry, husbandry, fishery, and so on. The results are of course affected by multiple factors such as technical and economic relation, marginal propensity to consume, ratio of resident income in total output, and so on. Because of the increasing relevance of industrial economic system, rapid development of public administration, social organization, education, technology, and the gradual reveal of effect on the policies of expanding domestic demand, the indirect and complete economic effects brought by meteorological service will continue to increase.While Zou, Lu, and Dong estimated the ratio of meteorological services effect (input-output ratio) for various industries, they did not calculate the economic effects [14]. As a result, we could not make a comparison between our results and theirs.


## 4.1. Sample and Data

Zou et al. conducted a research on the evaluation reports of meteorological services in Jiangxi from 2003 to 2007 using the traditional expert investigation method (Delphi method) [14], while our purpose is, by utilizing the input-output model for the data supplied with the 2007 input-output table of Jiangxi, to estimate quantitatively the economic effects rescued from the preventive strategies that are established based on the meteorological information and the interdependency between industrial economic systems. Our setting of the study is different from that of Zou et al. as outlined below.(1) Data of Input-Output. They are from “Input-output table of Jiangxi in 2007” and “Input-output table of China in 2007,” where the latter was compiled by the Economic Accounting Department of the National Bureau of Statistics of China in 2007. The table involves 2 branch classifications; one is a table of 42 industries and, the other, a table of 135 industries. In this paper we use the data of 135 industries. According to the research of Gu et al., the resident marginal propensity to consume c in 2007 was 0.66 [18].(2) Data on the Direct Economic Effect of Meteorological Services. Using the expert investigation method, Zou et al. estimated the meteorological service effect on agriculture, forestry, husbandry, and fishery, transportation, construction, production, and supply of electric power, gas, and water, and insurance, manufacturing, resident service, and other services, wholesale and retail sale in Jiangxi province [14]. To correspond to the names of 135 industries in input-output table, we process the same data but utilizing our comprehensive economic effect estimation method as follows.(a)
Zou, Lu, and Dong synthesized agriculture, forestry, husbandry, and fishery into one industry. In this paper we split it equally into five shares with the same average proportions of 3.61%.
(b)
In Zou, Lu, and Dong’s study, there was only an average proportion of direct service effect for general “manufacturing”. In this paper we use 54 kinds of manufacturing in the table of 135 industries with the same proportions of 0.512%.
(c)
In Zou, Lu, and Dong’s study, there was only an average proportion of “insurance.” Considering that “insurance” is a subkey of “finance” in the table of 135 industries, we equate “insurance” with “finance,” whose ratio of meteorological service effect in total output is 1.943%.
(d)
In Zou, Lu, and Dong’s study, there was only an average proportion of “transportation and warehousing.” In this paper we treat 8 subkeys of “transportation and warehousing” in the table of 135 industries whose proportions are all 2.454% equally.
(e)
In Zou, Lu, and Dong’s study, there was only a contribution rate of “resident service and other services.” According to the table of 135 industries, “resident service and other services” will be subdivided into “resident service” and “other services,” whose proportions are all 0.484%.Specific results are provided in Table2.Table 2
Contribution rate of weather service in highly sensitive industries in Jiangxi province, China (Measuring unit: %).
Industry
Direct service effect in 2003–2007
Contribution rate of meteorological service effect
Agriculture
4.07–3.15
3.61
Forestry
4.07–3.15
3.61
Animal husbandry
4.07–3.15
3.61
Fishery
4.07–3.15
3.61
Agriculture, forestry, husbandry, and fishery
4.07–3.15
3.61
Convenience food manufacturing
0.631–0.392
0.512
Milk and dairy manufacturing
0.631–0.392
0.512
Condiments and fermentation products manufacturing
0.631–0.392
0.512
Other food manufacturing
0.631–0.392
0.512
Alcohol and wine manufacturing
0.631–0.392
0.512
Textile product manufacturing
0.631–0.392
0.512
Knitwear, weaving, and its product manufacturing
0.631–0.392
0.512
Textile wearing apparel, footware, and cap manufacturing
0.631–0.392
0.512
Furniture manufacturing
0.631–0.392
0.512
Sport, cultural, and educational supply manufacturing
0.631–0.392
0.512
Basic chemical raw material manufacturing
0.631–0.392
0.512
Fertilizer manufacturing
0.631–0.392
0.512
Pesticide manufacturing
0.631–0.392
0.512
Coating, printing ink, paint, and similar product manufacturing
0.631–0.392
0.512
Synthetic material manufacturing
0.631–0.392
0.512
Special chemical product manufacturing
0.631–0.392
0.512
Daily chemical product manufacturing
0.631–0.392
0.512
Pharmaceutical manufacturing
0.631–0.392
0.512
Chemical fiber manufacturing
0.631–0.392
0.512
Cement, lime, and gypsum manufacturing
0.631–0.392
0.512
Cement and gypsum product manufacturing
0.631–0.392
0.512
Brick, stone, and other building material manufacturing
0.631–0.392
0.512
Glass and glassware manufacturing
0.631–0.392
0.512
Ceramic product manufacturing
0.631–0.392
0.512
Refractory product manufacturing
0.631–0.392
0.512
Graphite and other nonmetallic mineral product manufacturing
0.631–0.392
0.512
Nonferrous metal and alloy manufacturing
0.631–0.392
0.512
Boiler and prime mover manufacturing
0.631–0.392
0.512
Metalworking machinery manufacturing
0.631–0.392
0.512
Hoist-transportation machine manufacturing
0.631–0.392
0.512
Pumps, valves, compressors, and similar machinery manufacturing
0.631–0.392
0.512
Other common equipment manufacturing
0.631–0.392
0.512
Mining, metallurgy, and building equipment manufacturing
0.631–0.392
0.512
Chemical, wood, and nonmetal processing equipment manufacturing
0.631–0.392
0.512
Special machinery for agriculture, forestry, husbandry, and fishery manufacturing
0.631–0.392
0.512
Other specialized equipment manufacturing
0.631–0.392
0.512
Railway transport equipment manufacturing
0.631–0.392
0.512
Automobile manufacturing
0.631–0.392
0.512
Vessel and floating facility manufacturing
0.631–0.392
0.512
Other transportation equipment manufacturing
0.631–0.392
0.512
Motor manufacturing
0.631–0.392
0.512
Transmission and distribution and control equipment manufacturing
0.631–0.392
0.512
Wire, cable, fiber optic cable, and electrical equipment manufacturing
0.631–0.392
0.512
Household electric and nonelectric appliance manufacturing
0.631–0.392
0.512
Other electrical machinery and equipment manufacturing
0.631–0.392
0.512
Communication equipment manufacturing
0.631–0.392
0.512
Radar and radio equipment manufacturing
0.631–0.392
0.512
Electronic computer manufacturing
0.631–0.392
0.512
Electronic component manufacturing
0.631–0.392
0.512
Home audio-visual equipment manufacturing
0.631–0.392
0.512
Other electronic equipment manufacturing
0.631–0.392
0.512
Instrument manufacturing
0.631–0.392
0.512
Cultural and office machinery manufacturing
0.631–0.392
0.512
Craft and other product manufacturing
0.631–0.392
0.512
Production and supply of power and heat
2.323–1.569
1.946
Production and supply of gas
2.323–1.569
1.946
Production and supply of water
2.323–1.569
1.946
Construction
2.513–1.769
2.141
Railway transportation
2.993–1.914
2.454
Road transportation
2.993–1.914
2.454
City's public transportation
2.993–1.914
2.454
Water transportation
2.993–1.914
2.454
Air transportation
2.993–1.914
2.454
Pipeline transportation
2.993–1.914
2.454
Handling and other transport service
2.993–1.914
2.454
Warehousing
2.993–1.914
2.454
Wholesale and retail sale
0.44–0.15
0.295
Insurance
2.279–1.607
1.943
Resident service
0.655–0.312
0.484
Other service
0.655–0.312
0.484
Data source: Zou et al. [14].It should be pointed out that the Delphi method is a structured communication technique, originally developed as a systematic, interactive forecasting method which relies on a panel of experts and thus subject to and dependent on the knowledge of the participating experts. Hence, this method is more subjective in nature.Moreover, since the available meteorological service data sets for Jiangxi province from 2003 to 2007 are quite rich, the input-output method would be more appropriate. In fact, the Delphi (expert opinion) method is utilized only when there is a lack of sufficient information (due to its three drawbacks stated in Section1).In contrast, our estimation model (input-output method) for obtaining quantitative results regarding the comprehensive economic effects of meteorological services is established on the inhesion relevance among different industries, which is more objective and provides a practical setting for preventive strategies and other recommendations to rescue in the face of extreme weather conditions.Specifically, since the input-output table reflects more accurately the technical and economic relationships between industries in the national economy [13], it has become an ideal tool for calculating the associated and indirect economic effects of industries. According to the principle of doing certain things and refraining from doing other things, we present assessment models for associated, indirect, and complete economic effects based on the input-output table. Taking the meteorological service data in Jiangxi province in 2007 as an example, we obtained a series of results regarding the economic effects of meteorological services.


## 4.2. Results and Analysis

By utilizing the estimation equations of associated economic effect (7), indirect economic effect (11), and complete economic effect (13), we summarize the results in Table 3.Table 3
Results of economic effects (measuring unit: ten thousand RMB).
Industry
Direct service effect
Associated economic effect
Indirect economic effect
Complete economic effect
Agriculture
224274.860
32254.572
307400.052
415246.092
Forestry
45652.060
67369.404
68169.407
80815.325
Animal husbandry
157244.380
13094.821
180582.946
245308.922
Fishery
65774.200
2730.388
69725.861
80974.323
Service of agriculture, forestry, husbandry, and fishery
22176.230
36522.675
31415.316
34289.819
Coal mining and washing
/
29468.833
64986.176
106900.696
Oil and gas exploration
/
2002.814
59147.069
96862.943
Ferrous metal ore mining
/
3.147
15374.575
17790.070
Nonferrous metal mining
/
6192.810
27888.475
35079.747
Other nonmetal ore mining
/
180479.691
27467.146
31787.500
Grain grinding
/
40438.204
8231.043
22338.272
Feed processing
/
76422.147
29632.467
39312.748
Vegetable oil processing
/
7223.678
3069.876
11041.238
Sugar industry
/
354.072
11.208
86.284
Slaughtering and meat processing
/
4688.495
3631.551
16511.096
Aquatic product processing
/
886.262
1136.525
6718.374
Other food processing
/
603.799
1374.011
16120.633
Convenience food manufacturing
1294.285
188.289
1363.028
7520.514
Milk and dairy manufacturing
541.542
175.256
716.447
4223.064
Condiments and fermentation products manufacturing
1733.750
595.822
2805.411
5249.706
Other food manufacturing
4296.243
129.679
4683.159
25718.227
Alcohol and wine manufacturing
3949.839
742.590
6565.676
20779.630
Soft drink and refined tea processing
/
368.611
729.371
3786.235
Tobacco processing
/
90.931
205.572
14109.853
Cotton, chemical fiber textile and printing, and dyeing finishing
/
2263.104
11392.778
36670.132
Weaving, dyeing, and finishing
/
424.478
308.375
5435.661
Linen textile, silk spinning, and finishing
/
1519.773
2792.121
7674.866
Textile product manufacturing
2318.879
11662.786
7111.676
12948.707
Knitwear, weaving, and its product manufacturing
3286.149
1361.131
4670.416
7287.079
Textile wearing apparel, footware, and cap manufacturing
7537.976
18570.466
19011.769
43126.773
Leather, fur, feathers (fine hair), and its product manufacturing
/
1591.953
9140.069
30904.725
Timber, wood, bamboo, rattan, palm, and straw processing
/
51003.512
23097.462
38102.199
Furniture manufacturing
7927.270
13202.959
11774.138
20665.662
Paper and paper product manufacturing
/
3417.195
20861.898
45138.795
Printing and copying for recording medium
/
2752.207
4972.889
17553.695
Sport, cultural, and educational supply manufacturing
5552.497
12173.136
14409.494
22219.404
Oil and nuclear fuel processing
/
53732.201
45330.912
74672.808
Coking
/
134.923
30533.565
35546.660
Basic chemical raw material manufacturing
4313.508
7067.420
27771.611
37444.661
Fertilizer manufacturing
4776.596
113030.519
46324.485
60428.552
Pesticide manufacturing
3479.818
123788.558
30955.208
40371.197
Coating, printing ink, paint, and similar product manufacturing
2246.195
73507.519
12012.993
16516.688
Synthetic material manufacturing
4390.088
8384.865
20399.731
28660.573
Special chemical product manufacturing
5617.388
5959.214
32088.072
44742.483
Daily chemical product manufacturing
5380.403
3648.736
8484.226
20895.037
Pharmaceutical manufacturing
14668.068
4186.108
22027.422
29524.215
Chemical fiber manufacturing
5324.564
9295.692
13389.803
19345.855
Rubber product manufacturing
/
36257.879
16756.519
26013.082
Plastic product manufacturing
/
67906.036
19624.883
38499.650
Cement, lime, and gypsum manufacturing
8157.829
185923.581
40322.398
49618.238
Cement and gypsum product manufacturing
1465.631
230146.363
7133.046
7690.405
Brick, stone, and other building material manufacturing
934.492
144240.892
4230.565
7271.283
Glass and glassware manufacturing
3514.849
36133.173
16109.635
22741.921
Ceramic product manufacturing
1071.437
116648.089
3055.160
4717.192
Refractory product manufacturing
23.347
32815.366
108.039
121.212
Graphite and other nonmetallic mineral product manufacturing
1815.357
23832.294
5177.474
6063.783
Ironmaking
/
123.489
2086.748
2427.965
Steelmaking
/
92.345
9490.169
11074.714
Steel rolling processing
/
253850.953
192794.942
223013.850
Ferroalloy smelting
/
915.104
8348.284
9723.447
Nonferrous metal and alloy manufacturing
15380.644
8219.925
59352.409
72456.541
Nonferrous metal rolling process
/
16988.377
35441.068
45998.841
Metal product manufacturing
/
46209.909
18022.247
31824.760
Boiler and prime mover manufacturing
1585.843
15390.963
5216.272
6956.593
Metalworking machinery manufacturing
1317.524
8476.230
4777.305
6708.909
Hoist-transportation machine manufacturing
751.089
560.301
1799.648
2400.930
Pumps, valves, compressors, and similar machinery manufacturing
747.080
18494.049
3112.927
4196.952
Other common equipment manufacturing
2549.709
33004.312
15292.951
19117.583
Mining, metallurgy, and building equipment manufacturing
1225.585
34734.644
5878.842
7334.650
Chemical, wood, and nonmetal processing equipment manufacturing
153.743
1372.453
594.162
828.217
Special machinery for agriculture, forestry, husbandry, and fishery manufacturing
542.986
86045.197
5151.476
6327.882
Other specialized equipment manufacturing
10897.859
7327.467
47018.932
66889.403
Railway transport equipment manufacturing
186.199
18862.441
3037.940
4247.180
Automobile manufacturing
6337.792
31957.175
31643.484
46873.349
Vessel and floating facility manufacturing
2552.346
5227.158
4394.514
5606.492
Other transportation equipment manufacturing
2430.771
535.248
2891.412
6278.044
Motor manufacturing
2773.806
27926.379
13458.015
17086.261
Transmission, distribution, and control equipment manufacturing
1124.588
54310.877
6471.885
8334.190
Wire, cable, fiber optic cable, and electrical equipment manufacturing
4094.003
114155.168
16208.657
21175.912
Household electric and nonelectric appliance manufacturing
4924.380
23225.400
7882.982
17166.417
Other electrical machinery and equipment manufacturing
10017.357
14318.681
21735.315
27076.277
Communication equipment manufacturing
2352.241
2951.962
4628.916
10437.479
Radar and radio equipment manufacturing
181.233
1602.207
281.370
326.689
Electronic computer manufacturing
1193.221
17732.838
4494.400
9978.567
Electronic component manufacturing
5151.759
6807.819
17136.031
27029.060
Home audio-visual equipment manufacturing
3591.788
1461.821
4379.862
20785.160
Other electronic equipment manufacturing
871.793
6197.221
1338.956
1758.516
Instrument manufacturing
3068.764
9233.189
12540.223
17682.669
Cultural and office machinery manufacturing
603.192
48454.565
2153.542
3659.179
Craft and other product manufacturing
3195.546
66736.291
11051.372
16906.321
Scrap waste
/
236.007
330.902
416.647
Production and supply of power and heat
86655.828
26555.778
232416.262
384403.028
Production and supply of gas
830.203
2633.266
1794.680
3742.844
Production and supply of water
7733.696
37911.991
12831.484
21718.429
Construction
384517.177
783.857
398017.605
411185.018
Railway transportation
44262.798
34882.827
139320.673
198323.547
Road transportation
100498.662
54551.412
180734.309
225390.320
City's public transportation
8640.534
20198.200
12884.220
16904.497
Water transportation
2287.128
14447.927
4474.668
7291.585
Air transportation
3791.430
19799.388
7387.494
11854.599
Pipeline transportation
/
0.000
0.000
0.000
Handling and other transport service
1992.648
10219.544
3805.300
5947.536
Warehousing
2736.210
9417.221
3598.809
4164.856
The postal service
/
22052.628
2228.910
4591.521
Telecommunication and information transmission service
/
12765.332
12776.421
39300.447
Computer service
/
2211.991
1412.032
2692.011
Software
/
517.298
70.752
184.895
Wholesale and retail sale
28363.365
33103.282
171367.334
286838.534
Accommodation
/
20236.829
7528.296
16449.092
Catering
/
22786.509
25574.979
49250.285
Banking, security, and other financial activity
/
33651.299
46885.264
82681.399
Insurance
/
38477.101
5864.920
11096.667
Real estate
/
6902.654
18166.860
78204.631
Leasing
/
118605.765
835.384
2422.092
Business service
/
15666.721
6283.722
10785.177
Tourism
/
74.551
128.804
3505.748
Research and experimental development
/
117186.760
1598.279
1857.017
Professional and technical service
/
136052.891
4321.458
5614.004
Science and technology exchange and promotion service
/
20825.614
803.687
1126.383
Geological exploration
/
0.000
0.000
0.000
Water management
/
115937.570
2979.632
4471.497
Environmental management
/
9469.365
1190.529
2282.958
Public facilities management
/
523.006
110.174
1655.620
Resident service
2045.384
13369.132
5267.168
13544.352
Other service
3366.220
26964.684
20683.657
33635.381
Education
/
2670.063
8415.407
33121.785
Health
/
3211.955
15980.637
33957.909
Social security
/
7518.737
82.898
106.042
Social welfare
/
4109.687
92.954
114.111
Press and publication
/
30820.604
2182.198
4817.494
Radio, television, film, and motion picture
/
158.709
148.309
1230.560
Culture and art
/
23.727
0.957
553.198
Sport
/
0.000
0.000
109.717
Entertainment
/
18301.346
4832.876
8490.062
Public management and social organization
/
3246.067
5919.578
7626.480
Total
1388263.853
3952190.571
3399128.942
5010533.474An analysis of Table3 reaches the following conclusions.(1) Due to the technical and economic relations between industries, the direct economic effect of services can bring to all industries the associated, indirect, and complete economic effects. The direct economic effect of meteorological service in Jiangxi province in 2007 was 13882.63853 million RMB, which brought the associated economic effect of 39521.90571 RMB, indirect economic effect of 33991.28942 RMB, and complete economic effect of 50105.33474 RMB. Three economic effects, respectively, increased by 1.847-fold, 1.448-fold, and 2.609-fold.The ratio range of input in associated economic effect in Jiangxi province is about 1 : 85.41–1 : 145.197, the ratio range of input in indirect economic effect is about 1 : 73.44–1 : 124.848, and the ratio range of input in complete economic effect is about 1 : 108.27–1 : 183.059, which are remarkably different from a previous estimation based on the Delphi method (stated below).Ren studied the “Input-output table of China in 2007” for the whole country using the traditional Delphi method and concluded that the effect ratio range of input in output brought by meteorological services in China is 1:30–1:51 [19].In contrast, our results suggest that the associated, indirect and complete economic effects brought by meteorological services are so huge that more attention should be paid to this field.(2) As observed from the calculation of associated economic effect brought by direct economic effect, the top five industries, in order of decreasing proportions of associated effect are refractory product manufacturing (1405.538-fold), special machinery for agriculture, forestry, husbandry, and fishery manufacturing (158.467-fold), cement and gypsum product manufacturing (157.029-fold), brick, stone, and other building material manufacturing (154.352-fold), and ceramic product manufacturing (108.871-fold). The bottom five are construction (0.002-fold), other food manufacturing (0.030-fold), fishery (0.042-fold), animal husbandry (0.083-fold), and agriculture (0.144-fold).Also, from the calculation of indirect economic effect brought by direct economic effect, the top 5 industries in order of decreasing increments are railway transport equipment manufacturing (15.316-fold), fertilizer manufacturing (8.698-fold), special machinery for agriculture, forestry, husbandry, and fishery manufacturing (8.487-fold), pesticide manufacturing (7.896-fold), and basic chemical raw material manufacturing (5.438-fold). The bottom five construction (0.035-fold), convenience food manufacturing (0.053-fold), fishery (0.060-fold), other food manufacturing (0.090-fold), and animal husbandry (0.148-fold).Furthermore, as observed from the calculation of complete economic effect brought by direct economic effect, the top 5 industries in order of decreasing increments are railway transport equipment manufacturing (21.810-fold), fertilizer manufacturing (12.1651-fold), special machinery for agriculture, forestry, husbandry, and fishery manufacturing (10.654-fold), pesticide manufacturing (10.602-fold), and wholesale and retail sale (9.113-fold). The bottom five are construction (0.069), fishery (0.231), warehousing (0.522-fold), service of agriculture, forestry, husbandry, and fishery (0.546-fold), and animal husbandry (0.560-fold).Thus, increments of indirect and complete economic effects on traditional meteorological service objects such as construction, agriculture, forestry, husbandry, fishery, and warehousing are comparatively low, while some industries such as railway transport, equipment manufacturing, and fertilizer manufacturing can reach more indirect and complete economic effects. Consequently, in the future, meteorological service should tilt toward industries including railway transport, equipment manufacturing, and special machinery for agriculture, forestry, husbandry, and fishery manufacturing and provide more targeted fine services to improve their indirect and complete economic effects of meteorological service.(3) As seen from the calculation of complete economic effect brought by indirect economic effect, the top five industries in order of decreasing increments are culture and art (577.222-fold), tobacco processing (67.673-fold), tourism (26.218-fold), weaving, dyeing, and finishing (16.627-fold), and public facilities management (14.027-fold). The bottom six are construction (0.033-fold), cement and gypsum product manufacturing (0.078-fold), service of agriculture, forestry, husbandry, and fishery (0.092-fold), refractory product manufacturing (0.122-fold), steel rolling processing (0.157-fold), and ferrous metal ore mining (0.157-fold). It indicates that owing to the production-consumption-production cyclic effect, the output multipliers of industries like culture and art, tobacco processing, and tourism are bigger than those of construction, agriculture, forestry, husbandry, fishery, and so on. The results are of course affected by multiple factors such as technical and economic relation, marginal propensity to consume, ratio of resident income in total output, and so on. Because of the increasing relevance of industrial economic system, rapid development of public administration, social organization, education, technology, and the gradual reveal of effect on the policies of expanding domestic demand, the indirect and complete economic effects brought by meteorological service will continue to increase.While Zou, Lu, and Dong estimated the ratio of meteorological services effect (input-output ratio) for various industries, they did not calculate the economic effects [14]. As a result, we could not make a comparison between our results and theirs.


## 5. Concluding Remarks

In this paper we introduced the concepts of direct (associated, indirect, and complete) economic effect. Focusing our research on the direct consuming coefficient, the complete consuming coefficient, and Leontief inverse matrix, we have developed estimation methods for the associated, indirect, and complete economic effects. Using the meteorological services in Jiangxi province as a demonstrative example, the concepts and methods have been validated.The main findings include the following.(1)
Higher interdependency between economic systems of different industries exist, implying that the associated, indirect, and complete economic effects brought on by meteorological services could be much larger. For example, the ratio range of input in complete economic effect on meteorological services in Jiangxi province is about 1 : 108.27–1 : 183.059, which is larger than that of previous estimation using Delphi method (1 : 30–1:51), suggesting that the society as a whole should pay more attention to meteorological services.
(2)
Some industries with higher industrial connection ratios (Leontief inverse matrix), such as steel rolling processing, other nonmetal ore mining, and manufacturing, can achieve more associated, indirect, and complete economic effects. It follows that more attention should be paid to the meteorological services of these industries.
(3)
Increments of complete economic effect for some industries are relatively larger. These include railway transport, equipment manufacturing, fertilizer manufacturing, special agriculture machinery manufacturing, forestry, livestock, and fishery manufacturing, pesticide manufacturing, wholesale and retail sales, and other services. Consequently, governments should engage meteorological services in these areas.
(4)
Increments of indirect and complete economic effects on meteorological services traditionally directed to industries like construction, agriculture, forestry, livestock, and fishery, and warehousing are low. In the future, meteorological service providers should both expand their customer range and improve their quality of service in order to ultimately increase their comprehensive economic effects in these domains.The algorithms developed in this paper are characterized by the following strengths.(1)
When used in estimating the economic effects of meteorological services, the algorithms make it possible to fully consider the intrinsic relationship between industries; calculated comprehensive values are more scientific and credible.
(2)
The algorithms developed can rank the industries with the biggest increments and pick out highly sensitive industries. The results can provide references for development strategy and meteorological service investment decisions.
(3)
The algorithms can also be used for loss from weather events, for example, for the associated, indirect, and complete economic loss of industrial economic systems caused by disasters or sudden crises (e.g., the impact estimation of “911” event on US aviation). Similarly, the impact estimation for different carbon reduction policies on industrial economic systems, goal programming, and design of industrial regulations, all lend themselves to the use of the algorithms.Finally, there are still some concerns regarding the concepts, algorithms, and applications of associated, indirect, and complete economic effect estimation mentioned. In particular, the assumption that the relevance within industries is linear, rigid, and static may not reflect exactly reality of dynamic and complex industrial economic systems. To overcome such constraints assumed in the input-output method remains a major focus of future research.



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*Source: 904693-2014-01-21.xml*