FORECASTING FUTURE EMPLOYMENT OPPORTUNITIES FOR FOOD, AGRICULTURE, AND NATURAL RESOURCES HIGHER EDUCATION GRADUATES USING ADJUSTED BUREAU OF LABOR FORECASTS

Forecasts of the number of future professionals required for an ongoing safe, efficient US food system are highly important. The demand for adequately prepared higher education graduates must be met by the US Food, Agriculture, and Natural Resources Education System. Without accurate forecasts of the human resource needs of the food sector of the economy, adequate professionals may not be available when needed. This research effort makes use of Bureau of Labor Statistics (BLS) forecasted employment opportunities. The estimation of professionals required in the food and agriculture sectors of the economy is developed by selecting and manipulating data from the BLS model that is relevant to food and agriculture careers. These forecasts of needed professionals can be used by Directors of Resident Instruction to manage the educational system to meet the food sector demands for adequately educated human resources.employment, employment opportunities, food, agriculture, natural resources, directed graphs, education, bureau of labor, Labor and Human Capital,

When the Future is not what it used to be: Lessons from the Western European Experience to Forecasting Education and Training in Transition Economies

In an era of rapid technological change, information exchange, and emergence of knowledge-intensive industries it is critical to be able to identify the future skill needs of the labour market. Growing unemployment in EU member states and pre-accession countries in Eastern Europe combined with technological changes which make the skills of a significant number of workers obsolescent each year demand adequate knowledge of medium- and long-term demand for specific skills. Some EU members states have developed employment forecasting methods to identify future skill requirements which take account of the sectoral, occupational, and educational and training factors which influence supply and demand in the labour market for skills. A number of countries in Eastern Europe which are preparing to join the EU are interested in developing employment forecasting models that would provide them with similar information relating to skills. Taking account of the requirements of the Single European Market and increasing international mobility, it is desirable that the pre-accession countries should develop models which, if possible, are comparable with existing methods of forecasting training and qualification needs in existing member states of the EU. This task requires regular medium-term forecasts which will extend the time horizon of decision makers beyond the current economic cycle, be applicable to the whole economy, allow speedy adjustment to changing circumstances, and which will take account of relevant factors such as investment plans, output and labour productivity forecasts, and technological change. The objective of this paper is to provide a summary of existing methods and data sets used to forecast education and training needs in four members of the European Union, in order to motivate similar work in three pre-accession countries. We first provide a detailed account of the different approaches to forecast education and training needs in France, Germany, Ireland and The Netherlands. For each of these countries, we consider the labour market data on which employment forecasts are based and the current methods in use, examine how data reliability and accuracy of forecasts are dealt with, and discuss the dissemination and usage of forecast information generated by those systems. We then look at the same range of issues for three pre-accession Central European countries (Czech Republic, Poland and Slovenia.) The paper concludes by suggesting a number of needed actions in preparation for developing an approach to forecasting education and training needs in the three pre-accession countries.http://deepblue.lib.umich.edu/bitstream/2027.42/39650/3/wp265.pd

When the Future is not what it used to be: Lessons from the Western European Experience to Forecasting Education and Training in Transition Economies

In an era of rapid technological change, information exchange, and emergence of knowledge-intensive industries it is critical to be able to identify the future skill needs of the labour market. Growing unemployment in EU member states and pre-accession countries in Eastern Europe combined with technological changes which make the skills of a significant number of workers obsolescent each year demand adequate knowledge of medium- and long-term demand for specific skills. Some EU members states have developed employment forecasting methods to identify future skill requirements which take account of the sectoral, occupational, and educational and training factors which influence supply and demand in the labour market for skills. A number of countries in Eastern Europe which are preparing to join the EU are interested in developing employment forecasting models that would provide them with similar information relating to skills. Taking account of the requirements of the Single European Market and increasing international mobility, it is desirable that the pre-accession countries should develop models which, if possible, are comparable with existing methods of forecasting training and qualification needs in existing member states of the EU. This task requires regular medium-term forecasts which will extend the time horizon of decision makers beyond the current economic cycle, be applicable to the whole economy, allow speedy adjustment to changing circumstances, and which will take account of relevant factors such as investment plans, output and labour productivity forecasts, and technological change. The objective of this paper is to provide a summary of existing methods and data sets used to forecast education and training needs in four members of the European Union, in order to motivate similar work in three pre-accession countries. We first provide a detailed account of the different approaches to forecast education and training needs in France, Germany, Ireland and The Netherlands. For each of these countries, we consider the labour market data on which employment forecasts are based and the current methods in use, examine how data reliability and accuracy of forecasts are dealt with, and discuss the dissemination and usage of forecast information generated by those systems. We then look at the same range of issues for three pre-accession Central European countries (Czech Republic, Poland and Slovenia.) The paper concludes by suggesting a number of needed actions in preparation for developing an approach to forecasting education and training needs in the three pre-accession countries.employment forecasting, education and training needs forecasting, labor market, transition

Forecasting volatility in commodity markets

Commodity prices have historically been among the most volatile of international prices. Measured volatility (the standard deviation of price changes) has not been below 15 percent and at times has been more than 50 percent. Often the volatility of commodity prices has exceeded that of exchange rates and interest rates. The large price variations are caused by disturbances in demand and supply. Stockholding leads to some price smoothing, but when stocks are low, prices can jump sharply. As a result, commodity price series are not stationary and in some periods they jump abruptly to high levels or fall precipitously to low levels relative to their long-run average. Thus it is difficult to determine long-term price trends and the underlying distribution of prices. The volatility of commodity prices makes price forecasting difficult. Indeed, realized prices often deviate greatly from forecasted prices, which has led to the practice of giving forecasts probability ranges. But assigning probability ranges requires forecasting future price volatility, which, given uncertainties about true price distribution, is difficult. One potentially useful source of information for forecasting volatility is the volatility forecasts imbedded in the prices of options written on commodities traded in exchanges. Options give the holder the right to buy (call) or sell (put) a certain commodity at a certain date at a fixed (exercise) price. Options prices depend on several variables, one of which is the expected volatility up to the maturity date. Given a specific theoretical model, the market prices of options can be used to derive the market's expectations about price volatility and the price distribution. The authors systematically analyze different methods'abilities to forecast commodity price volatility (for several commodities). They collected the daily prices of commodity options and other variables for seven commodities (cocoa, corn, cotton, gold, silver, sugar, and wheat). They extracted the volatility forecasts implicit in options prices using several techniques. They compared several volatility forecasting methods, divided into three categories: (1) forecasts using only expectations derived form options prices; (2) forecasts using only time-series modeling; (3) forecasts that combine market expectations and time-series modeling (a new method devised for this purpose). They find that the volatility forecasts produced by method 3 outperform the first two as well as the naive forecast based on historical volatility. This result holds both in and out of sample for almost all commodities considered.Markets and Market Access,Access to Markets,Economic Theory&Research,Economic Forecasting,Science Education

Forecasting the labour market by occupation and education: Some key issues

In this paper, we focus on two key characteristics of ROA’s forecasting approach of the labour market by occupation and education. These concern the use of the gap approach, and the substitution of education programmes within occupations. We show that the gap between supply and demand constitutes a useful and informative concept, which can be justifiably used as long as too little is known about the adjustment process in the labour market. Then we discuss the structure of the substitution process, mainly focusing on substitution as a result of the initially expected gaps between supply and demand. We distinguish between active substitution, resulting from supply-demand mismatches for the education programme concerned, and passive substitution, which is due to spillover effects from supply-demand mismatches for other education programmes. Passive substitution between education programmes is included in the forecasts when the final gaps between supply and demand are calculated. Recent ROA forecasts are used to illustrate the meaning of the various substitution processes for expected labour demand and the gaps between supply and demand. We find that omitting substitution demand from the forecasting model results in future labour market prospects that are generally too pessimistic for the higher educated.education, training and the labour market;

Labour Market Information for Educational Investments

A well-trained workforce is generally seen as an important precondition for economic growth. But decisions about investments in education and training must be taken under uncertainty, because the benefits will only be reaped in the long term. To predict what these future benefits may be, it is necessary to have some insight into how the labour market functions with respect to education and training. There are various theories, in the literature, which outline a picture of the role played by education and training in the labour market. This paper begins with a sketch of the various policy approaches to the match between the education system and the labour market and an explanation of the importance of labour market information for policy choices. Five labour market theories in which workers'' educational backgrounds is an important factor will be described. Then, on the basis of these theories, we infer what labour market information could be significant in educational decisions. Some basic principles for the preparation of labour market forecasts are identified, and a structure which could be used in making forecasts is outlined. The paper concludes with a plea for a European approach.education, training and the labour market;

The Deskilling vs Upskilling Debate: The Role of BLS Projections

[Excerpt] The growing shortage of professionally trained workers and the rising skill premiums will tend to cause supply to increase more rapidly than we have projected. But the gap between the projected growth of demand and supply is huge. Just to maintain the balance between the growth of supply and the growth of occupational demand that prevailed in the 1980s, itself a period of shortage, it will be necessary to increase in the stock of college graduates in the year 2000 by 3.7 million or, put another way, to raise the number of college graduates entering the labor forces by 462,000 or 42 percent between 1992 and the year 2000