PRIMERA ETAPA

The information necessary for model elaboration is summarized in the data array used in the research:

• Data obtained directly from the information sources, • Data obtained trough calculations:

− Aggregated data and data recalculated according to the methodological modifications,

− Evaluations.

The direct data was received from the data source without additional processing, for instance, “Number of inhabitants and forecasts thereof in one-year age groups”. The aggregated data were calculated, by summarizing the initial information, for instance, “Number of filled positions in all professions at 37 profession groups”. According to the methodological alterations, calculated were, for instance, “those employed at principal and additional work” and “those employed at full and partial time”. Evaluations were necessary for calculating such indices, about which information is not available in such degree of detailed elaboration that is necessary for the forecasting models. For instance, data about distribution of the employed in on–year age groups and in 37 profession groups during the time frame from 1997 until 2005. The evaluations were isolated as a separate data group with a purpose to provide with an option to evaluate the data credibility.

Table 15. Contents of the data array used in the research

Title of the parameter Data source information Manner of

obtainment Information users Inhabitants

Forecasts of inhabitant count in one-year

age groups Eurostat Data directly from the obtained information source

Forecasting models in MS Excel environment DOM in Powersim Studio environment

Employment

Quotients of economic activity in age

groups Eurostat CSP Data obtained directly from the information source

DOM in Powersim Studio environment

Number of the filled positions, number of the employed in Latvia in sectors and in 37 profession groups from year 1997 until year 2005

CSP Calculation data DOM in Powersim Studio environment

Average gross monthly salary, LVL from

1997 until 2005 CSP Calculation data environment DOM in Powersim Studio Division of the number of the unemployed

according to the last profession from year 2003 until year 2005

NVA Data obtained

directly from the information source

DOM in Powersim Studio environment

Number of the employed on January 1,

2006 in 37 profession groups DDA Calculation data environment DOM in Powersim Studio Number of the employed on January 1, 2006

in 37 profession groups and age groups DDA Calculation data environment DOM in Powersim Studio Number of vacant positions on January 1,

2006 in 37 profession groups

DDA Calculation data DOM in Powersim Studio environment

Number of vacant positions on January 1, 2006 in types of economic activity (sectors)

DDA Calculation data DOM in Powersim Studio environment

Number of vacant positions on January 1, 2006 in types of economic activity and 37 profession groups

DDA Calculation data DOM in Powersim Studio environment

Distribution of the employed in 37 profession groups and one-year age groups in year 2006

DŅA Calculation data Forecasting models in MS Excel environment DOM in Powersim Studio environment

Distribution of the employed according to types of economic activity and in one-year age groups in year 2006

DŅA Calculation data Forecasting models in MS Excel environment Distribution of the employed in 37

profession groups and in one-year age groups from year 1997 until year 2005

DŅA, CSP – ”Labor force survey”

Evaluation Forecasting models in MS Excel environment Distribution of the employed according

to the types of economic activity and in one-year age groups from year 1997 until year 2005

DŅA, CSP – ”Labor force survey”

Evaluation Forecasting models in MS Excel environment Distribution of the respondents according to

the answer on a question about changes during the last 7 years of life in 37 profession groups from year 1999 until year 2005

DŅA Calculation data Forecasting models in MS Excel environment Distribution of the respondents according

to the answer on a question about changes during the last 7 years of life in 37 profession groups and in one-year age groups from year 1999 until year 2005

DŅA Evaluation Forecasting models in MS Excel environment

Title of the parameter Data source information Manner of obtainment

Information users Education

Number of students according to the

education levels and programs IZM Data directly from the obtained information source

Forecasting models in MS Excel environment DOM in Powersim Studio environment

Number of admitted students according to the education levels and programs

IZM Data obtained

directly from the information source

DOM in Powersim Studio environment

Data about prior education of those

admitted to certain education level IZM Data directly from the obtained information source

DOM in Powersim Studio environment

Number of graduates from educational establishments according to the education levels and programs

IZM Forecasting models in

MS Excel environment DOM in Powersim Studio environment

Number of state financed study positions in

education levels and study programs IZM DOM in Powersim Studio environment Number of study positions in education

levels and study programs

IZM DOM in Powersim Studio

environment Tuition in education levels and study

programs

GDP

GDP according to the types of economic

activity, mill. LVL CSP Data directly from the obtained information source

DOM in Powersim Studio environment

GDP growth forecasts Researches of the 1st

component

Data obtained directly from the information source

DOM in Powersim Studio environment

Capital growth forecasts Researches of

the 1st

component

Data obtained directly from the information source

DOM in Powersim Studio environment

Detailed labor force demand forecasts in 37 aggregated profession groups from year 2007 until year 2014, year 2020, and year 2030

Researches of the 1st

component

Data obtained directly from the information source

DOM in Powersim Studio environment

Environment and resources

Investments in environmental protection according to industries

Volume of emissions (tons) in industries Energy consumption (petroleum equivalent of a ton) in industries

CSP Data obtained

directly from the information source

DOM in Powersim Studio environment

For creation of data array used in the research (See Table 15), past data were arranged according to the model elaboration requirements and data available in the future, the existing data were recognized, and missing data were identified, additionally necessary data were received from DDA and DŅA.

For obtaining past data the following was performed:

− Calculation of the dynamic row parameters, according to the changes of methodical character,

− In cases when more detailed data is necessary, the parameter evaluation was ensured, by applying statistical methods, based on information of various (compatible) data (secondary and primary) sources.

Further special surveys are not necessary for functioning of forecasting models. Information, which is to additionally acquired is obtained during the already occurring surveys, for instance, in CSP Labor force survey, Profession survey, additionally about work, 2nd work (quarterly), by supplementing to the existing questionnaires and by increasing the number of respondents. It is important to further obtain data about distribution of the employed according to types of economic activities, professions, and one-year age groups, as well as according to the profession of the employed one year before.

Figure 18. Data to be used in forecasting

Obtainment of future parameters necessary for model elaboration is scheduled from the following information sources (See Figure 18):

• Labor force demand:

− CSP “Profession survey”; − NVA “Employer survey”; • Labor force supply:

− CSP “Labor force survey”.

Information about labor force supply

Information about labor force supply hereinafter is planned to be received from the data of Labor force survey. Information for forecasting models in profession section is necessary to a four sign code degree of detailed elaboration, according to the LR Profession classifier code in types of economic activity and one-year age groups. The profession section in four sign code is necessary, in order to calculate the parameters for the forecasting models in division of the elaborated 37 profession groups. Therefore, in order to obtain representative information during the Labor force surveys, which is necessary for the forecasting models, it is desirable to ensure the volume of selection to be around 50-60 thousand inhabitants. The volume of selection of medium-term forecasts could be additionally increased (total selection reaching 80 thousand), in order to obtain even more detailed forecasts in regional section.

Information about labor force demand

Hereinafter, the information necessary for forecasting models is scheduled to be received from the Profession survey data performed by CSP. In year 2006, the questions of the Profession survey were included in the Salary structure survey. The questionnaire of the survey (Report on salary structure in year 2006, 5th work. Part B. Data about employees) is necessary to be supplemented with a feature characterizing the employees: principal work – 1; additional work – 2.

The parameters are necessary in order to preclude interruption in the employee count dynamics, because, beginning with reports of year 2004, the number of employees in an enterprise (institution, organization) is divided into those working full time and those working part time. In previous years, the number of employees in CSP reports was divided into those working at a principal job and at an additional job.

Report about job (quarterly), 2nd work (chapter 4). The number of the employees and vacant positions in professions is preferable to be obtained at a greater degree of detailed elaboration.

The volume of the selections in Profession surveys would have to be maintained at least to the existing extent.

CSP and NVA have accumulated significant experience in arranging selection surveys. Experience shows that data obtained are becoming more complete by every year, furthermore, by acquiring additional financing, the volume of selection and the number of the survey questions could be increased. Thus, the customer can receive the necessary information on a regular basis.