Nate Silver, The Signal and the Noise: Why So Many Predictions Fail And Some Don’t” (NY: Penguin Press, 2012), 454 pages.
Nate Silver gained national attention with a forecasting system he developed in 2003 called PECOTA. He used baseball data to forecast the performance of major league baseball players. It was very successful and the attention he got allowed him the time and money to expand his interests into other areas and write us a thoughtful and reflective book on forecasting.
The Signal and the Noise is a book for people who like data and the possibilities for using it in the latest information revolution brought on by cheap and powerful computers. In the Introduction Silver tells a precautionary tale from the first information revolution that came in 1440 with the printing press. Before the printing press knowledge was lost without some way to store it; after the printing press knowledge could be stored but ideas could also be circulated to make arguments to the masses and promote controversies like Martin Luther’s ninety-five theses. The printing and distribution of 300 thousand copies brought centuries of religious warfare.
Silver uses the introduction to make similar contrasts and set up a philosophy of forecasting. Forecasting implies planning with uncertainty that needs prudence, wisdom and industriousness along with a dose of humility. Silver thinks of forecasting as an on-going process of revision where the risk of failure is always present but the possibility of progress makes it worth the trouble.
The book has 13 chapters. The first chapter titled “A Catastrophic Failure of Prediction” describes what went wrong with the predictions for the recent stock market and housing bubbles. Then it is on to six more chapters on prediction for political polls, baseball, weather, earthquakes, economic forecasting and swine flu.
The topics all have a random and unpredictable element for something we would like to predict in advance. Silver gives readers some historical background, some basic theory or science where it’s relevant and then an assessment of the forecasting record: weather forecasting, better, earthquake forecasting, no progress, and so on. Each chapter suggests a common principle or two of success or failure that turns into a general theory and practice of forecasting by the end of the book.
Chapter 8 introduces Bayesian statistical inference in a descriptive form to be applied to six more topics of prediction: gambling, chess, poker, stock prices, greenhouse effects and terrorism. Bayesian inference is a branch of statistics that uses prior probability to make a new probability estimate, the posterior probability. Silver tries to convince readers to think of Bayes as a procedural method that combines new evidence with prior beliefs in a repeated process of revision.
Given the variety of topics from technology and the social and physical sciences readers will prefer some topics over others. I spent more time on the economics chapters. In Chapter 6 Silver does what forecasters hope no one will do: he goes back to check and compare old forecasts. Most are way off but being a labor forecaster I appreciate Silver’s precautions: correlation does not mean causation, explanatory variables change frequently, never throw out data, tell a story using credible economic reasoning.
I especially liked the comments he used of Jan Hatzius, chief economist at Goldman-Sachs. His correct forecast of the 2007 financial collapse resulted from looking at mortgage data and evaluating the size of the leveraged mortgage market and the risk of default from unqualified buyers. At page 196 Silver writes “Hatzius refers to this chain of cause and effect as a ‘story.’ It is a story about the economy – and although it might be a data-driven story, it is one grounded in the real world.”
Chapter 11 takes a close look at the age old question: Can you make money predicting stock prices? Those who believe in markets always answer no, but Silver uses the volumes of stock data to do a variety of fun experiments comparing strategies - buy and hold, manic momentum and a few more – before reaching that conclusion.
The Signal and the Noise is a very readable statistics book with good graphics, thorough documentation and source notes. I would never have predicted publication of a general audience book with so much detail but as I finished reading I decided the volume of data on the Internet promotes a wider interest along with wider access. The growing combination of access and interest make it a timely book that suggests a structure and philosophy for people who want to pursue their own interests and separate the signal from the noise.
Wednesday, July 17, 2013
Monday, July 8, 2013
Inflation and Wages for 2006 to 2012
News of college graduates struggling to pay student loans draws attention to wages. College graduates who cannot find jobs using their college degree skills add to the pool of labor looking for already low wage jobs, potentially lowering wages and buying power even more.
Wages need to keep up with inflation to assure Americans can buy what they produce and keep themselves employed. In practice comparing wages over time requires adjusting wages for inflation with the Consumer Price Index to compare buying power, or real wages. For example, the median wage of Accountants and Auditors was $55,650 in 2006, but to keep up with inflation and have the same buying power in 2012 median wages would have to be $62,188. Instead they were $63,550, a 2.19 percent increase in real wages over the six year period. Data are from the Bureau of Labor Statistics, Occupational Employment Survey, which reports wages for 22 occupational categories and 829 occupations. The self employed are not included here.
Accountants and auditors are the ideal because jobs are up; averaging a little over six thousand new jobs a year with wages up faster than inflation. The outcome for retail salesperson and cashier was the opposite: jobs and real wages declined. The median wage of retail salespersons was $19,760 in 2006, but to keep up with inflation the 2012 median wage needed to be $22,494. Instead it was $21,110, a 6.15 percent decrease in real wages.
The median wage of cashier was $16,810 in 2006, but to keep up with inflation in 2012 median wages needed to be $19,136. Instead they were $18,970, a .87 percent decrease in real wages. Retail salesperson remains America’s biggest occupation with 4.3 million jobs but jobs keep declining; cashier continues to be the second largest occupation with 3.3 million jobs, but also with declining employment.
Retail salesperson and cashier are two of 388 occupations I can find that did not keep up with inflation between 2006 and 2012. These 388 occupations employed 72.5 million in 2006, but only 69.4 million in 2012. Because total employment is down between 2006 and 2012 only a little over 61 million show higher real wages in 2012. I used 2006 as the last full year before the housing bubble and then the recession, but other years could show better or worse results compared to inflation.
The wage data applies to jobs at establishments at the time of the survey and not to people’s wages or income, which are part of another survey. Because jobs turnover, some of the people in low wage occupations in 2006 may well have moved into higher skilled and higher wage occupations by 2012. Therefore, the data allow conclusions about wage inequality but limited conclusions about income inequality.
The results and selected details outlined below suggest two broad statements about wages for the six year period. First, the highest wage occupations in 2006 in upper level management, most of finance and professional occupations have real wage gains by 2012, while the lowest wage occupations in 2006 were the most likely to have lower real wages in 2012. Second, the real wage gains of occupations with wage gains had modest gains, less than one percent a year in a majority of cases. In the United States, working for wages is a tough way to make a living.
Selected Details by Occupational Category-----------------------------
Managerial occupations and financial occupations had the ideal with more jobs and a composite of wages for both occupational categories showing individual occupations mostly keeping up with inflation or with a percent or two increase in real wages. There are exceptions. Managerial occupations had wage gains above inflation for 27 of 36 occupations. General operations managers, food service managers, accommodations managers and construction managers were exceptions. Financial occupations had real wage gains in 24 of 33 occupations. Exceptions included personal financial advisors and real estate appraisers, both down.
Professional occupations did well compared to inflation, although generally a modest 1 to 3 percent increase in real wages for computing and mathematics occupations. Computer programmers are an exception, down slightly. Real wages were down for architects and landscape architects and up for 16 of 18 engineering specialties. Both lawyers and paralegals show a 2.5 to 4 percent decline in real wages. More jobs in legal services and lower real wages suggest the supply is out running demand in law.
Education, training and library occupations had job growth and higher real wages for 46 of 65 occupations in education, training and library. College teaching had higher real wages with some exceptions for professors of education, foreign languages, agricultural and biological sciences. Graduate assistants also had falling real wages. Teaching positions in the public schools had job losses in these years but real wages were up 1 to 3 percent for both elementary and secondary teaching with exceptions in some vocational and special education positions. Librarian lost jobs and buying power to inflation.
Health care occupations had job growth and 45 of 60 occupations with higher real wages. Licensed physicians, pharmacists, therapists, technicians and technologists did well against inflation but there are notable exceptions. Median wages for chiropractors, podiatrists, optometrists, opticians and dentists did not keep up with inflation. Dentists in general practice have high wages, but to keep up with inflation their median wage would need to be $150,421 in 2012. Instead it was $145,240, a -3.44 percent decrease in real wages for the six years. Dental hygienist also lost buying power to inflation.
Registered nurses have 2.6 million jobs, the most in health care and the fifth largest United States occupation. Median wages kept up with inflation, but just barely, rising by .41 percent to $65,470 in 2012. Health care aides and assistants lost buying power even though they are already low paid occupations. For example, nurses aides needed a 2012 wage of $25,248 to keep up with inflation, but it was $24,420, a 3.28 percent decline from 2006.
Home health aides, medical assistants, occupational therapy aides, physical therapy aides, pharmacy aides also lost buying power. The low paid health care occupations have declining real wages and increasing employment suggesting a large increase in the supply of people flooding into low wage jobs because they can not find anything else.
Protective service occupations, food preparation and serving related occupations, personal care and service occupations had more jobs in 2012 than 2006, but 16 of 22 occupations in protective services had lower real wages. Occupations as firefighters, correctional officers and jailors, bailiffs, detectives and security guards along with their supervisory staff had falling real wages. Security guards have over a million jobs, but median wages needed to be$24,508 in 2012 to keep with inflation. Instead they were $23,970, a 2.2 percent decrease in real wages.
Food preparation and serving related occupations had a mix where 10 of 18 occupations with higher real wages along with more jobs. Fast food cooks had the lowest median wage of $15,410 in 2006. Their wages were up more than inflation but they remain the lowest paid job in food services with 2012 median wages of only $18,410. All other categories of restaurant, cafeteria, and even private household cooks have declining real wages. Median wages for waiters, waitresses and combined food preparation and serving workers did better, up more than inflation by 2 to 9 percent, but still only in the low twenties for wages.
Personal care and service occupations had more jobs but lost buying power to inflation in 21 of 33 occupations. Non-farm animal caretakers – typically dog walking services, ushers, lobby attendants, ticket takers, amusement park and recreation workers, barbers and hairdressers, child care workers, personal care aides, recreation workers, and residential advisors had combined 2012 employment of almost 3 million jobs and all with declining real wages.
There were eight more occupational categories with declining employment and generally declining real wages.
Building and grounds cleaning and maintenance occupations had declining real wages in 8 of 10 occupations; janitors and cleaners, maids and housekeeping cleaners, landscaping and grounds maintenance and their supervisory staff among them. Janitors and cleaners have over 2 million jobs, but needed median wages at least $22,687 to keep up with inflation by 2012. Instead they were $22,320, a 1.62 percent decline.
Sales occupations had 17 of 22 occupations with declining real wages including salespersons and cashiers previously mentioned and parts salespersons, advertising, insurance, securities, commodities, and financial services sales agents, real estate brokers and agents and telemarketers.
Office and Administrative support occupations had a few bright spots, but 29 of 55 occupations had declining real wages. Financial support occupations like bookkeeping, accounting, and auditing clerks fared the best with 1 to 2 percent gains in real wages. However, communications operators for directory assistance, long distance, call center and answering services have lower real wages and lower dollar wages. Customer service representatives have over two million jobs, but their 2006 median wage of $28,330 needed to be $32,249 in 2012 to keep up with inflation. Instead it was $30,580, a 5.18 percent decrease in real wages. Receptionists, legal secretaries, desktop publishers, and a selection of shipping, receiving and order clerks had falling real wages between 2006 and 2012.
Farming, fishing, and forestry occupations had fewer jobs and declining real wages in 7 of 14 occupations. Farm workers and crop, nursery and greenhouse laborers were all jobs with declining real wages along with most of logging operations jobs.
Construction occupations did badly with 29 of 59 occupations losing buying to inflation and all the skilled trades like masons, carpenters, drywall installers showing lower real wages and some also lower dollar wages.
Repair and installation occupations had 2 to 6 percent real declines for 33 of 52 individual occupations including automotive and vehicle repair occupations, home appliance repair, telecommunications repair and a few more.
Production occupations had declining employment and 61 of 115 occupations had lower real wages. Team assemblers have 1.2 million jobs, the biggest production occupation. Median wages kept up with inflation, but just barely, rising by .38 percent to $27,640 in 2012. Otherwise assembly and fabrication occupations like electrical and electronic assemblers, engine and machine assemblers had declining real wages from 2006 to 2012.
Other production occupations with declining real wages were in metal and plastic work for jobs as machinists, tool and die makers, machine operators for cutting, grinding, drilling, and buffing; in food processing for jobs as bakers, meat, poultry, and fish cutters and trimmers, slaughterers and meat packers; in apparel and finishing jobs as sewers, upholstery and textile machine operators.
Transportation and moving occupations had declining employment and 28 of 52 occupations with falling real wages. Hand laborers and freight, stock, and material movers have almost 2.4 million jobs, but their 2006 median wage of $21,220 needed to be $24,156 in 2012 to keep up with inflation. Instead it was $23,890, a 1.1 percent decrease in real wages.
Airline pilots and flight attendants, traffic controllers, locomotive engineers, most railroad jobs, and many driving jobs including heavy and tractor trailer drivers, industrial truck and tractor operators and school bus drivers had declining real wages. Pilots, copilots, and flight engineers had median wages of $141,090 in 2006, but to keep up with inflation and have the same buying power in 2012 median wages would have to be $160,200. Instead they were $114,200, a 28.90 percent decrease.
Flight attendants had median wages of $53,780 in 2006, but to keep up with inflation and have the same buying power in 2012 median wages would have to be $61,220. Instead they were $37,240, a 39.17 percent decrease, the biggest decrease I can find among United States occupations.
Wages need to keep up with inflation to assure Americans can buy what they produce and keep themselves employed. In practice comparing wages over time requires adjusting wages for inflation with the Consumer Price Index to compare buying power, or real wages. For example, the median wage of Accountants and Auditors was $55,650 in 2006, but to keep up with inflation and have the same buying power in 2012 median wages would have to be $62,188. Instead they were $63,550, a 2.19 percent increase in real wages over the six year period. Data are from the Bureau of Labor Statistics, Occupational Employment Survey, which reports wages for 22 occupational categories and 829 occupations. The self employed are not included here.
Accountants and auditors are the ideal because jobs are up; averaging a little over six thousand new jobs a year with wages up faster than inflation. The outcome for retail salesperson and cashier was the opposite: jobs and real wages declined. The median wage of retail salespersons was $19,760 in 2006, but to keep up with inflation the 2012 median wage needed to be $22,494. Instead it was $21,110, a 6.15 percent decrease in real wages.
The median wage of cashier was $16,810 in 2006, but to keep up with inflation in 2012 median wages needed to be $19,136. Instead they were $18,970, a .87 percent decrease in real wages. Retail salesperson remains America’s biggest occupation with 4.3 million jobs but jobs keep declining; cashier continues to be the second largest occupation with 3.3 million jobs, but also with declining employment.
Retail salesperson and cashier are two of 388 occupations I can find that did not keep up with inflation between 2006 and 2012. These 388 occupations employed 72.5 million in 2006, but only 69.4 million in 2012. Because total employment is down between 2006 and 2012 only a little over 61 million show higher real wages in 2012. I used 2006 as the last full year before the housing bubble and then the recession, but other years could show better or worse results compared to inflation.
The wage data applies to jobs at establishments at the time of the survey and not to people’s wages or income, which are part of another survey. Because jobs turnover, some of the people in low wage occupations in 2006 may well have moved into higher skilled and higher wage occupations by 2012. Therefore, the data allow conclusions about wage inequality but limited conclusions about income inequality.
The results and selected details outlined below suggest two broad statements about wages for the six year period. First, the highest wage occupations in 2006 in upper level management, most of finance and professional occupations have real wage gains by 2012, while the lowest wage occupations in 2006 were the most likely to have lower real wages in 2012. Second, the real wage gains of occupations with wage gains had modest gains, less than one percent a year in a majority of cases. In the United States, working for wages is a tough way to make a living.
Selected Details by Occupational Category-----------------------------
Managerial occupations and financial occupations had the ideal with more jobs and a composite of wages for both occupational categories showing individual occupations mostly keeping up with inflation or with a percent or two increase in real wages. There are exceptions. Managerial occupations had wage gains above inflation for 27 of 36 occupations. General operations managers, food service managers, accommodations managers and construction managers were exceptions. Financial occupations had real wage gains in 24 of 33 occupations. Exceptions included personal financial advisors and real estate appraisers, both down.
Professional occupations did well compared to inflation, although generally a modest 1 to 3 percent increase in real wages for computing and mathematics occupations. Computer programmers are an exception, down slightly. Real wages were down for architects and landscape architects and up for 16 of 18 engineering specialties. Both lawyers and paralegals show a 2.5 to 4 percent decline in real wages. More jobs in legal services and lower real wages suggest the supply is out running demand in law.
Education, training and library occupations had job growth and higher real wages for 46 of 65 occupations in education, training and library. College teaching had higher real wages with some exceptions for professors of education, foreign languages, agricultural and biological sciences. Graduate assistants also had falling real wages. Teaching positions in the public schools had job losses in these years but real wages were up 1 to 3 percent for both elementary and secondary teaching with exceptions in some vocational and special education positions. Librarian lost jobs and buying power to inflation.
Health care occupations had job growth and 45 of 60 occupations with higher real wages. Licensed physicians, pharmacists, therapists, technicians and technologists did well against inflation but there are notable exceptions. Median wages for chiropractors, podiatrists, optometrists, opticians and dentists did not keep up with inflation. Dentists in general practice have high wages, but to keep up with inflation their median wage would need to be $150,421 in 2012. Instead it was $145,240, a -3.44 percent decrease in real wages for the six years. Dental hygienist also lost buying power to inflation.
Registered nurses have 2.6 million jobs, the most in health care and the fifth largest United States occupation. Median wages kept up with inflation, but just barely, rising by .41 percent to $65,470 in 2012. Health care aides and assistants lost buying power even though they are already low paid occupations. For example, nurses aides needed a 2012 wage of $25,248 to keep up with inflation, but it was $24,420, a 3.28 percent decline from 2006.
Home health aides, medical assistants, occupational therapy aides, physical therapy aides, pharmacy aides also lost buying power. The low paid health care occupations have declining real wages and increasing employment suggesting a large increase in the supply of people flooding into low wage jobs because they can not find anything else.
Protective service occupations, food preparation and serving related occupations, personal care and service occupations had more jobs in 2012 than 2006, but 16 of 22 occupations in protective services had lower real wages. Occupations as firefighters, correctional officers and jailors, bailiffs, detectives and security guards along with their supervisory staff had falling real wages. Security guards have over a million jobs, but median wages needed to be$24,508 in 2012 to keep with inflation. Instead they were $23,970, a 2.2 percent decrease in real wages.
Food preparation and serving related occupations had a mix where 10 of 18 occupations with higher real wages along with more jobs. Fast food cooks had the lowest median wage of $15,410 in 2006. Their wages were up more than inflation but they remain the lowest paid job in food services with 2012 median wages of only $18,410. All other categories of restaurant, cafeteria, and even private household cooks have declining real wages. Median wages for waiters, waitresses and combined food preparation and serving workers did better, up more than inflation by 2 to 9 percent, but still only in the low twenties for wages.
Personal care and service occupations had more jobs but lost buying power to inflation in 21 of 33 occupations. Non-farm animal caretakers – typically dog walking services, ushers, lobby attendants, ticket takers, amusement park and recreation workers, barbers and hairdressers, child care workers, personal care aides, recreation workers, and residential advisors had combined 2012 employment of almost 3 million jobs and all with declining real wages.
There were eight more occupational categories with declining employment and generally declining real wages.
Building and grounds cleaning and maintenance occupations had declining real wages in 8 of 10 occupations; janitors and cleaners, maids and housekeeping cleaners, landscaping and grounds maintenance and their supervisory staff among them. Janitors and cleaners have over 2 million jobs, but needed median wages at least $22,687 to keep up with inflation by 2012. Instead they were $22,320, a 1.62 percent decline.
Sales occupations had 17 of 22 occupations with declining real wages including salespersons and cashiers previously mentioned and parts salespersons, advertising, insurance, securities, commodities, and financial services sales agents, real estate brokers and agents and telemarketers.
Office and Administrative support occupations had a few bright spots, but 29 of 55 occupations had declining real wages. Financial support occupations like bookkeeping, accounting, and auditing clerks fared the best with 1 to 2 percent gains in real wages. However, communications operators for directory assistance, long distance, call center and answering services have lower real wages and lower dollar wages. Customer service representatives have over two million jobs, but their 2006 median wage of $28,330 needed to be $32,249 in 2012 to keep up with inflation. Instead it was $30,580, a 5.18 percent decrease in real wages. Receptionists, legal secretaries, desktop publishers, and a selection of shipping, receiving and order clerks had falling real wages between 2006 and 2012.
Farming, fishing, and forestry occupations had fewer jobs and declining real wages in 7 of 14 occupations. Farm workers and crop, nursery and greenhouse laborers were all jobs with declining real wages along with most of logging operations jobs.
Construction occupations did badly with 29 of 59 occupations losing buying to inflation and all the skilled trades like masons, carpenters, drywall installers showing lower real wages and some also lower dollar wages.
Repair and installation occupations had 2 to 6 percent real declines for 33 of 52 individual occupations including automotive and vehicle repair occupations, home appliance repair, telecommunications repair and a few more.
Production occupations had declining employment and 61 of 115 occupations had lower real wages. Team assemblers have 1.2 million jobs, the biggest production occupation. Median wages kept up with inflation, but just barely, rising by .38 percent to $27,640 in 2012. Otherwise assembly and fabrication occupations like electrical and electronic assemblers, engine and machine assemblers had declining real wages from 2006 to 2012.
Other production occupations with declining real wages were in metal and plastic work for jobs as machinists, tool and die makers, machine operators for cutting, grinding, drilling, and buffing; in food processing for jobs as bakers, meat, poultry, and fish cutters and trimmers, slaughterers and meat packers; in apparel and finishing jobs as sewers, upholstery and textile machine operators.
Transportation and moving occupations had declining employment and 28 of 52 occupations with falling real wages. Hand laborers and freight, stock, and material movers have almost 2.4 million jobs, but their 2006 median wage of $21,220 needed to be $24,156 in 2012 to keep up with inflation. Instead it was $23,890, a 1.1 percent decrease in real wages.
Airline pilots and flight attendants, traffic controllers, locomotive engineers, most railroad jobs, and many driving jobs including heavy and tractor trailer drivers, industrial truck and tractor operators and school bus drivers had declining real wages. Pilots, copilots, and flight engineers had median wages of $141,090 in 2006, but to keep up with inflation and have the same buying power in 2012 median wages would have to be $160,200. Instead they were $114,200, a 28.90 percent decrease.
Flight attendants had median wages of $53,780 in 2006, but to keep up with inflation and have the same buying power in 2012 median wages would have to be $61,220. Instead they were $37,240, a 39.17 percent decrease, the biggest decrease I can find among United States occupations.
Wednesday, June 26, 2013
Computer Support Specialists
Computer Support Specialists have two occupations
Standard Occupational Classification #15-1151 Computer User Support Specialists
Standard Occupational Classification #15-1152 Computer Network Support Specialists
SOC Definition for #15-1151-- Provide technical assistance to computer users. Answer questions or resolve computer problems for clients in person, or via telephone or electronically. May provide assistance concerning the use of computer hardware and software, including printing, installation, word processing, electronic mail, and operating systems.
Examples of other common names in use -- Computer Customer Support Specialist, Help Desk Representative, Help Desk Specialist, Desktop Support Specialist, End-User Support Specialist, Help Desk Analyst, Help Desk Technician, PC Support Specialist.
SOC Definition for #15-1152-- Analyze, test, troubleshoot, and evaluate existing network systems, such as local area network (LAN), wide area network (WAN), and Internet systems or a segment of a network system. Perform network maintenance to ensure networks operate correctly with minimal interruption.
Examples of other common names in use -- Network Diagnostic Support Specialist, Network Support Technician, Network Technician; excludes Network and Computer Systems Administrators #15-1142 and Computer Network Architects #15-1143.
National 2012 employment as Computer User Support Specialists was 525,630 and for Computer Network Support Specialists were 167,980 for a combined total 693,610. Both jobs were reported together as a combination in the years from 2000 to 2011. The combined category had growth of 14 thousand new jobs a year since 2000 at growth rates well above the national average. The Bureau of Labor Statistics is forecasting modest job growth of 11 thousand per year through 2020 for the combined category.
Job growth is not the only measure of new hiring. Job openings equal job growth and the number of net replacements. Net replacements are people who permanently leave an occupation for another occupation or retirement and must be replaced before there can be any job growth. Job openings for Computer User and Network Specialists have been around 26.9 per year in recent years.
The recently updated BLS Education and Training Classification assignments for network and user support specialists list some college training in computer sciences without necessarily have a degree as the entry level education minimum. However, percentages from survey data are published for the network and user support occupations showing an educational distribution where 29 percent have some college, but no degree, and almost 41 percent have an associate’s degree, or baccalaureate degree and 8 percent above the BA. Previous experience is considered unnecessary, but moderate on-the-job training is expected to be necessary for new hires.
Computer User Support Specialists
Computer User Support Specialists have at least some employment in almost every industry, but a dozen selected industries have almost 60 percent of the jobs. Computer design and related activities has almost 20 percent, 103 thousand jobs. Education, including colleges, has another 12.5 percent, a little over 65 thousand jobs. Software publishers and data processing employ 6.5 percent, or 34 thousand jobs. Management of Companies have 28 thousand jobs, combined employment services and business support services another 28 thousand, and Federal, state and local governments 23.6 thousand.
The basic wage data from the BLS occupational employment survey includes a wage distribution. Averages are not used much in wage data. A few high wages pull up the average and make it unrepresentative. Instead a distribution range of wages is published with the 10th, 25th, median, 75th, and 90th percentiles of wages. A 10th percentile wage means 10 percent working in this job have wages equal to or less than the 10th percentile wage and so on. Annual wages are converted to hourly wages by dividing annual by 2080.
The 2012 entry wage for the national market in the 10th percentile for Computer User Support Specialists is reported as $27,620 in 2012. The 25th percentile wage equals $35,790. The median wage is $46,240, the 75th percentile wage equals $60,400 and the 90th percentile wage is $77,430.
For the 103,820 Computer User Support Specialists in Computer Design and Related Services the 2012 10th percentile entry wage is $27,230. The 25th percentile wage equals $35,290. The median wage is $46,690, the 75th percentile wage equals $62,630 and the 90th percentile wage is $83,030.
Computer Network Support Specialists
Computer Network Support Specialists also have some employment in almost every industry but a dozen industries have a little over 60 percent of the jobs. Computer design and related activities has almost 21 percent, or 34.7 thousand jobs. Software publishers, communications carriers and data processing have another 13.2 percent, or 22.3 thousand jobs. Education, including colleges, employ 11 thousand; government another 11 thousand; Management of Companies 9.6 thousand jobs. About 5,000 are employed through employment agencies.
The entry wage for the national market in the 10th percentile for Computer Network Support Specialists is reported as $34,930 in 2012. The 25th percentile wage equals $44,530. The median wage is $59,090, the 75th percentile wage equals $76,450 and the 90th percentile wage is $96,850.
For the 34,700 Computer Network Support Specialists in Computer Design and Related Services the 2012 10th percentile entry wage is $34,140. The 25th percentile wage equals $44,960. The median wage is $60,050, the 75th percentile wage equals $79,890 and the 90th percentile wage is $101,170.
Standard Occupational Classification #15-1151 Computer User Support Specialists
Standard Occupational Classification #15-1152 Computer Network Support Specialists
SOC Definition for #15-1151-- Provide technical assistance to computer users. Answer questions or resolve computer problems for clients in person, or via telephone or electronically. May provide assistance concerning the use of computer hardware and software, including printing, installation, word processing, electronic mail, and operating systems.
Examples of other common names in use -- Computer Customer Support Specialist, Help Desk Representative, Help Desk Specialist, Desktop Support Specialist, End-User Support Specialist, Help Desk Analyst, Help Desk Technician, PC Support Specialist.
SOC Definition for #15-1152-- Analyze, test, troubleshoot, and evaluate existing network systems, such as local area network (LAN), wide area network (WAN), and Internet systems or a segment of a network system. Perform network maintenance to ensure networks operate correctly with minimal interruption.
Examples of other common names in use -- Network Diagnostic Support Specialist, Network Support Technician, Network Technician; excludes Network and Computer Systems Administrators #15-1142 and Computer Network Architects #15-1143.
National 2012 employment as Computer User Support Specialists was 525,630 and for Computer Network Support Specialists were 167,980 for a combined total 693,610. Both jobs were reported together as a combination in the years from 2000 to 2011. The combined category had growth of 14 thousand new jobs a year since 2000 at growth rates well above the national average. The Bureau of Labor Statistics is forecasting modest job growth of 11 thousand per year through 2020 for the combined category.
Job growth is not the only measure of new hiring. Job openings equal job growth and the number of net replacements. Net replacements are people who permanently leave an occupation for another occupation or retirement and must be replaced before there can be any job growth. Job openings for Computer User and Network Specialists have been around 26.9 per year in recent years.
The recently updated BLS Education and Training Classification assignments for network and user support specialists list some college training in computer sciences without necessarily have a degree as the entry level education minimum. However, percentages from survey data are published for the network and user support occupations showing an educational distribution where 29 percent have some college, but no degree, and almost 41 percent have an associate’s degree, or baccalaureate degree and 8 percent above the BA. Previous experience is considered unnecessary, but moderate on-the-job training is expected to be necessary for new hires.
Computer User Support Specialists
Computer User Support Specialists have at least some employment in almost every industry, but a dozen selected industries have almost 60 percent of the jobs. Computer design and related activities has almost 20 percent, 103 thousand jobs. Education, including colleges, has another 12.5 percent, a little over 65 thousand jobs. Software publishers and data processing employ 6.5 percent, or 34 thousand jobs. Management of Companies have 28 thousand jobs, combined employment services and business support services another 28 thousand, and Federal, state and local governments 23.6 thousand.
The basic wage data from the BLS occupational employment survey includes a wage distribution. Averages are not used much in wage data. A few high wages pull up the average and make it unrepresentative. Instead a distribution range of wages is published with the 10th, 25th, median, 75th, and 90th percentiles of wages. A 10th percentile wage means 10 percent working in this job have wages equal to or less than the 10th percentile wage and so on. Annual wages are converted to hourly wages by dividing annual by 2080.
The 2012 entry wage for the national market in the 10th percentile for Computer User Support Specialists is reported as $27,620 in 2012. The 25th percentile wage equals $35,790. The median wage is $46,240, the 75th percentile wage equals $60,400 and the 90th percentile wage is $77,430.
For the 103,820 Computer User Support Specialists in Computer Design and Related Services the 2012 10th percentile entry wage is $27,230. The 25th percentile wage equals $35,290. The median wage is $46,690, the 75th percentile wage equals $62,630 and the 90th percentile wage is $83,030.
Computer Network Support Specialists
Computer Network Support Specialists also have some employment in almost every industry but a dozen industries have a little over 60 percent of the jobs. Computer design and related activities has almost 21 percent, or 34.7 thousand jobs. Software publishers, communications carriers and data processing have another 13.2 percent, or 22.3 thousand jobs. Education, including colleges, employ 11 thousand; government another 11 thousand; Management of Companies 9.6 thousand jobs. About 5,000 are employed through employment agencies.
The entry wage for the national market in the 10th percentile for Computer Network Support Specialists is reported as $34,930 in 2012. The 25th percentile wage equals $44,530. The median wage is $59,090, the 75th percentile wage equals $76,450 and the 90th percentile wage is $96,850.
For the 34,700 Computer Network Support Specialists in Computer Design and Related Services the 2012 10th percentile entry wage is $34,140. The 25th percentile wage equals $44,960. The median wage is $60,050, the 75th percentile wage equals $79,890 and the 90th percentile wage is $101,170.
Friday, May 24, 2013
A Shortage of Manufacturing Skills?
President Carter’s domestic policy advisor, Stuart Eizenstat, and Robert Lerman, an Urban Institute Fellow, claim there is a skills gap in manufacturing that threatens America’s manufacturing comeback. [“Bring back the apprentice”, Washington Post, May 5, 2013, and republished on yahoo] Readers are asked to accept a citation from an unnamed survey that claims 600,000 jobs go unfilled because the skills gap is real and America needs an apprenticeship program. They worry “We are at risk of squandering this historic opportunity – mainly because firms interested in investing in the United States are finding too few workers with the skills needed . . .”
Really?
American manufacturing dropped 2.2 million jobs in the recession months from January 2008 until February 2010. Every single manufacturing sub-sector lost jobs. Since February 2010 the manufacturing recovery is confined to primary and fabricated metals, manufacturing for machinery, and transportation equipment but nothing else. All other sub-sectors combined had a net loss of jobs as small job gains in a few sub-sectors were not enough to offset losses in others. From February 2012 to the end of last year manufacturing is up only 491 thousand jobs, less than a quarter of the recessionary losses. With 2.2 million jobs lost in the recession and 491 thousand new jobs in the recovery, the difference suggests a surplus of production workers available for hire, not a shortage.
The Bureau of Labor Statistics lists just four occupations in primary and fabricated metals, machinery and transportation equipment manufacturing that require 12 months or more of on-the-job training: machinist, metal and plastic model makers, metal and plastic pattern makers, and tool and die makers.
Machinists were reported to have 388 thousand jobs as of 2012, but there were 419 thousand machinist jobs in 2008. The authors cite “a dearth of machinists” when 31 thousand machinists laid off in the recession appear available to hire now: a surplus not a shortage.
Model makers had 5,700 jobs in 2012; pattern makers 4,130 jobs. In 2008 there were almost 9,000 jobs as model makers; over 6,000 pattern makers. These are small niche jobs but recessionary layoffs suggest a surplus available to hire, not shortage.
Tool and die makers were reported with 76 thousand jobs as of 2012, but there were almost 86 thousand in 2008. Tool and die maker jobs are up from 70 thousand in 2011, but the increase disguises a long term decline. There were 100 thousand tool and die maker jobs in 2005 and 131 thousand in 2000. Bureau of Labor Statistics reported jobs suggest a surplus of tool and die makers, not a shortage.
The four occupations above that need long term on-the-job training are among 26 production occupations the Bureau of Labor Statistics includes in a category called metal and plastic workers. In 2008, 2.15 million had jobs in these 26 occupations; only 1.84 million in 2012. These 26 occupations require no more than a high school degree as defined and published in the Bureau of Labor Statistics education and training classification. An apprenticeship requirement is defined in the training classification but not necessary for any of the 26 occupations.
The other 22 metal and plastic work occupations require no more than moderate-on-the-training defined as “competency in an occupation that can be acquired during 1 to 12 months of combined on-the-job experience and informal training. The 22 include welders, cutters, solderers, and brazers, and computer numerically controlled machine tool programmers the authors cite as needing an apprentice program.
Assemblers and fabricators are another major category of production worker with 10 occupations and 1.98 million jobs in 2008 but only 1.72 million jobs in 2012. That leaves 260,000 available to hire, another surplus. None of these ten occupations require long term on-the-job training: six need moderate term on-the-job training, four need only short term on-the-job training defined as a month or less of combined on-the-job experience and informal training.
Eizenstat and Lerman make no use of Bureau of Labor Statistics data to support their claims because the data shows a surplus with no need for apprenticeship programs. When a business complains about a shortage of labor, they mean a shortage at the low wage they expect to offer. Instead of bidding up the wage to get the help they want, business moves to far off places like Bangladesh, and then finds a willing or gullible economist to blame the unemployed, who would have a job if they just had the right skills.
Alan Greenspan, the former Fed chair, perfected the “Get some training” propaganda in his capital hill testimony. He was calm and self assured when he placed the blame for unemployment on the unemployed. These guys like drama: “squandering this historic opportunity.” Oh Please! Where is Oprah when we need her?
Really?
American manufacturing dropped 2.2 million jobs in the recession months from January 2008 until February 2010. Every single manufacturing sub-sector lost jobs. Since February 2010 the manufacturing recovery is confined to primary and fabricated metals, manufacturing for machinery, and transportation equipment but nothing else. All other sub-sectors combined had a net loss of jobs as small job gains in a few sub-sectors were not enough to offset losses in others. From February 2012 to the end of last year manufacturing is up only 491 thousand jobs, less than a quarter of the recessionary losses. With 2.2 million jobs lost in the recession and 491 thousand new jobs in the recovery, the difference suggests a surplus of production workers available for hire, not a shortage.
The Bureau of Labor Statistics lists just four occupations in primary and fabricated metals, machinery and transportation equipment manufacturing that require 12 months or more of on-the-job training: machinist, metal and plastic model makers, metal and plastic pattern makers, and tool and die makers.
Machinists were reported to have 388 thousand jobs as of 2012, but there were 419 thousand machinist jobs in 2008. The authors cite “a dearth of machinists” when 31 thousand machinists laid off in the recession appear available to hire now: a surplus not a shortage.
Model makers had 5,700 jobs in 2012; pattern makers 4,130 jobs. In 2008 there were almost 9,000 jobs as model makers; over 6,000 pattern makers. These are small niche jobs but recessionary layoffs suggest a surplus available to hire, not shortage.
Tool and die makers were reported with 76 thousand jobs as of 2012, but there were almost 86 thousand in 2008. Tool and die maker jobs are up from 70 thousand in 2011, but the increase disguises a long term decline. There were 100 thousand tool and die maker jobs in 2005 and 131 thousand in 2000. Bureau of Labor Statistics reported jobs suggest a surplus of tool and die makers, not a shortage.
The four occupations above that need long term on-the-job training are among 26 production occupations the Bureau of Labor Statistics includes in a category called metal and plastic workers. In 2008, 2.15 million had jobs in these 26 occupations; only 1.84 million in 2012. These 26 occupations require no more than a high school degree as defined and published in the Bureau of Labor Statistics education and training classification. An apprenticeship requirement is defined in the training classification but not necessary for any of the 26 occupations.
The other 22 metal and plastic work occupations require no more than moderate-on-the-training defined as “competency in an occupation that can be acquired during 1 to 12 months of combined on-the-job experience and informal training. The 22 include welders, cutters, solderers, and brazers, and computer numerically controlled machine tool programmers the authors cite as needing an apprentice program.
Assemblers and fabricators are another major category of production worker with 10 occupations and 1.98 million jobs in 2008 but only 1.72 million jobs in 2012. That leaves 260,000 available to hire, another surplus. None of these ten occupations require long term on-the-job training: six need moderate term on-the-job training, four need only short term on-the-job training defined as a month or less of combined on-the-job experience and informal training.
Eizenstat and Lerman make no use of Bureau of Labor Statistics data to support their claims because the data shows a surplus with no need for apprenticeship programs. When a business complains about a shortage of labor, they mean a shortage at the low wage they expect to offer. Instead of bidding up the wage to get the help they want, business moves to far off places like Bangladesh, and then finds a willing or gullible economist to blame the unemployed, who would have a job if they just had the right skills.
Alan Greenspan, the former Fed chair, perfected the “Get some training” propaganda in his capital hill testimony. He was calm and self assured when he placed the blame for unemployment on the unemployed. These guys like drama: “squandering this historic opportunity.” Oh Please! Where is Oprah when we need her?
Wednesday, May 15, 2013
Executive Administrative Assistants
Executive Secretaries and Executive Administrative Assistants
Standard Occupational Classification #43-6011 Executive Secretaries and Executive Administrative Assistants
SOC Definition--Provide high-level administrative support by conducting research, preparing statistical reports, handling information requests, and performing clerical functions such as preparing correspondence, receiving visitors, arranging conference calls, and scheduling meetings. May also train and supervise lower-level clerical staff.
Examples of other common names in use—Executive Assistant, Administrative Assistant
Executive Secretaries and Executive Administrative Assistants excludes jobs as
43-6012 Legal secretaries, as 43-6013 medical secretaries and as 43-6014 other types of secretaries such as alumni secretary, department secretary, office secretary, personal secretary, school secretary, real estate assistant.
Executive secretaries and executive administrative assistants are sprinkled through almost every sector and sub-sector of the economy. They typically account for only a half percent or less of firm staffing, but selected service sectors are as high six and seven percent. Securities, commodity contracts, and other financial investments establishments have an average of 5.5 to 7 percent staffing of executive secretaries and executive administrative assistants. Various real estate specialty service firms, grant making and giving services, social advocacy organizations, business, professional, labor, political, and similar organizations all have 4 to 6 percent staffing with executive secretaries and executive administrative assistants.
National employment as executive secretaries and executive administrative assistants dropped to 803,040 in 2012. Jobs are down from 1.37 million since 2000 in a steady decline, but job totals for medical secretaries and secretaries except executive, legal and medical are up enough to maintain employment totals for the combined category. The job total for all secretarial and administrative assistant categories continues to hold at 3.6 to 3.7 million in the national market since 2000. The Bureau of Labor Statistics is forecasting modest job growth of 15.6 thousand per year in spite of the decade long decline.
The recently updated BLS Education and Training Classification assignments for Executive Secretaries and Executive Administrative Assistants list high school diploma or equivalent as the entry level education minimum. However, percentages from survey data are published for the executive secretary and executive administrative assistant occupation. Results show an educational distribution where 35 percent have some college, but no degree, and almost 30 percent have an associate’s degree, or baccalaureate degree and a few percent above the BA. Many executive assistants need computer skills beyond word processing that add to necessary education and enhance employability. In general on-the-job training is expected to be minimal for this occupation; applicants need to bring the skills and experience to the job.
Job growth is not the only measure of new hiring. Job openings equal job growth and the number of net replacements. Net replacements are people who permanently leave an occupation for another occupation or retirement and must be replaced before there can be any job growth. Job openings for Executive Secretaries and Executive Administrative Assistants are expected to average around 32,180 per year in the years up to 2020..
The basic wage data from the BLS occupational employment survey includes a wage distribution. Averages are not used much in wage data. A few high wages pull up the average and make it unrepresentative. Instead a distribution range of wages is published with the 10th, 25th, median, 75th, and 90th percentiles of wages. A 10th percentile wage means 10 percent working in this job have wages equal to or less than the 10th percentile wage and so on. Annual wages are converted to hourly wages by dividing annual by
The entry wage for the national market in the 10th percentile for Executive Secretaries and Executive Administrative Assistants is reported as $31,310 in 2012. The 25th percentile wage equals $38,030. The median wage is $47,500, the 75th percentile wage equals $60,130 and the 90th percentile wage is $73,530. Yearly reported wage increases are keeping up with inflation across the whole salary distribution with a small increase in buying power over the last decade.
There are 27,380 Executive Secretaries and Executive Administrative Assistants jobs in the Washington Metropolitan area for 2012. The entry wage for the Washington Metropolitan market in the 10th percentile for Executive Secretaries and Executive Administrative Assistants is reported as $36,640 in 2012. The 25th percentile wage equals $43,790. The median wage is $55,420, the 75th percentile wage equals $69,460 and the 90th percentile wage is $83,360. Legal secretaries earn more; medical and other secretaries earn less than executive secretaries and executive administrative assistants in the Washington metropolitan area.
There are 9,740 Executive Secretaries and Executive Administrative Assistants jobs in the Washington DC for 2012. The entry wage for the Washington DC market in the 10th percentile for Executive Secretaries and Executive Administrative Assistants is reported as $34,180 in 2012. The 25th percentile wage equals $41,100. The median wage is $51,470, the 75th percentile wage equals $66,970 and the 90th percentile wage is $84,440. Legal secretaries earn more; medical and other secretaries earn less than executive secretaries and executive administrative assistants in Washington DC.
Standard Occupational Classification #43-6011 Executive Secretaries and Executive Administrative Assistants
SOC Definition--Provide high-level administrative support by conducting research, preparing statistical reports, handling information requests, and performing clerical functions such as preparing correspondence, receiving visitors, arranging conference calls, and scheduling meetings. May also train and supervise lower-level clerical staff.
Examples of other common names in use—Executive Assistant, Administrative Assistant
Executive Secretaries and Executive Administrative Assistants excludes jobs as
43-6012 Legal secretaries, as 43-6013 medical secretaries and as 43-6014 other types of secretaries such as alumni secretary, department secretary, office secretary, personal secretary, school secretary, real estate assistant.
Executive secretaries and executive administrative assistants are sprinkled through almost every sector and sub-sector of the economy. They typically account for only a half percent or less of firm staffing, but selected service sectors are as high six and seven percent. Securities, commodity contracts, and other financial investments establishments have an average of 5.5 to 7 percent staffing of executive secretaries and executive administrative assistants. Various real estate specialty service firms, grant making and giving services, social advocacy organizations, business, professional, labor, political, and similar organizations all have 4 to 6 percent staffing with executive secretaries and executive administrative assistants.
National employment as executive secretaries and executive administrative assistants dropped to 803,040 in 2012. Jobs are down from 1.37 million since 2000 in a steady decline, but job totals for medical secretaries and secretaries except executive, legal and medical are up enough to maintain employment totals for the combined category. The job total for all secretarial and administrative assistant categories continues to hold at 3.6 to 3.7 million in the national market since 2000. The Bureau of Labor Statistics is forecasting modest job growth of 15.6 thousand per year in spite of the decade long decline.
The recently updated BLS Education and Training Classification assignments for Executive Secretaries and Executive Administrative Assistants list high school diploma or equivalent as the entry level education minimum. However, percentages from survey data are published for the executive secretary and executive administrative assistant occupation. Results show an educational distribution where 35 percent have some college, but no degree, and almost 30 percent have an associate’s degree, or baccalaureate degree and a few percent above the BA. Many executive assistants need computer skills beyond word processing that add to necessary education and enhance employability. In general on-the-job training is expected to be minimal for this occupation; applicants need to bring the skills and experience to the job.
Job growth is not the only measure of new hiring. Job openings equal job growth and the number of net replacements. Net replacements are people who permanently leave an occupation for another occupation or retirement and must be replaced before there can be any job growth. Job openings for Executive Secretaries and Executive Administrative Assistants are expected to average around 32,180 per year in the years up to 2020..
The basic wage data from the BLS occupational employment survey includes a wage distribution. Averages are not used much in wage data. A few high wages pull up the average and make it unrepresentative. Instead a distribution range of wages is published with the 10th, 25th, median, 75th, and 90th percentiles of wages. A 10th percentile wage means 10 percent working in this job have wages equal to or less than the 10th percentile wage and so on. Annual wages are converted to hourly wages by dividing annual by
The entry wage for the national market in the 10th percentile for Executive Secretaries and Executive Administrative Assistants is reported as $31,310 in 2012. The 25th percentile wage equals $38,030. The median wage is $47,500, the 75th percentile wage equals $60,130 and the 90th percentile wage is $73,530. Yearly reported wage increases are keeping up with inflation across the whole salary distribution with a small increase in buying power over the last decade.
There are 27,380 Executive Secretaries and Executive Administrative Assistants jobs in the Washington Metropolitan area for 2012. The entry wage for the Washington Metropolitan market in the 10th percentile for Executive Secretaries and Executive Administrative Assistants is reported as $36,640 in 2012. The 25th percentile wage equals $43,790. The median wage is $55,420, the 75th percentile wage equals $69,460 and the 90th percentile wage is $83,360. Legal secretaries earn more; medical and other secretaries earn less than executive secretaries and executive administrative assistants in the Washington metropolitan area.
There are 9,740 Executive Secretaries and Executive Administrative Assistants jobs in the Washington DC for 2012. The entry wage for the Washington DC market in the 10th percentile for Executive Secretaries and Executive Administrative Assistants is reported as $34,180 in 2012. The 25th percentile wage equals $41,100. The median wage is $51,470, the 75th percentile wage equals $66,970 and the 90th percentile wage is $84,440. Legal secretaries earn more; medical and other secretaries earn less than executive secretaries and executive administrative assistants in Washington DC.
Saturday, May 11, 2013
The $9.00 an hour minimum
The Obama Administration recently proposed an increase in the minimum wage to $9.00 an hour. The current minimum continues at $7.25 an hour where it has been since July 24th 2009, the date of the last of three planned increases passed by Congress. The proposed increase is a little over 24 percent over the three years from 2009 to 2012, more than inflation but still hardly a self supporting wage.
At $9.00 an hour per full time employee the increase converts $3,640 [$1.75 x 2,080] of profit to cost per full time minimum wage employee. To employers of low wage jobs like ushers, lobby attendants, ticket takers, shampooers, or child care workers higher wage costs bring pressure to experiment with higher prices, and fewer work hours or jobs. Raising prices might raise revenue and restore profits as long as sales don’t fall by much. Otherwise cutting jobs or hours in response to a higher minimum wage should help restore profits.
Since everyone agrees higher wages do pressure employers to cut work hours or jobs for employees paid below the minimum wage that part makes for easy agreement. However, it represents a small part of the minimum wage debate, unless economists and their business clients expect job losers to disappear, never to work again.
In their book Minimum Wages economists David Neumark and William L. Wascher write on page 116, “. . . as we emphasized earlier in this chapter the potential for minimum wage increases to affect wages higher in the wage distribution is also important in assessing the effects of minimum wage policy.” (1)
When the minimum wage jumped by $2.10 an hour from 2006 to 2009, jobs as fast food cooks dropped from 612 thousand to 539 thousand. (2) During the same period there were other jobs as cashiers, retail salespersons, rental and counter clerks and others with wage ranges above the minimum. An increase in applications for these other jobs quite likely holds down wages as economists like to predict from any increase in supply, but in wage ranges above the minimum. As people find other jobs in other industries and occupations the higher minimum wage can work to increase employment at higher wages.
In spite of their conclusions, Neumark and Wascher “. . . find it very difficult to see good economic rationale for continuing to seek a higher minimum wage.” In this they are like all economists who have been reciting conclusions like that for decades. Telling people they are worse off with a higher wage makes it necessary to quickly convince the public that jobs will be lost.
Neumark and Wascher and other economists try to convince people by theorizing in the specialized terminology of the economics fraternity. At page 254 they write “In the model, an increase in the nominal wage that raises the wage rate of unskilled labor not only induces substitution of skilled for unskilled labor, it also leads to substitution of unionized skilled labor for non-unionized skilled labor because the union sector expands and the nonunion sector contracts.” Their predictions come without mention of occupations like cashier, clerk or fast food cook and lead to conclusions applied to generic markets of products and jobs. The authors might recognize the millions of opportunities to move from low wage to higher wage employment by looking at wage distributions by occupation reported by the U. S. Bureau of Labor Statistics in their Occupational Employment Survey.
Business predictably opposes a higher minimum wage year after year. For individual business a higher minimum wage always converts profits to costs, even though the economy needs people with income to put back in the spending stream. Economists repeatedly offer theoretical support as though they are paid spokesmen or women.
Telling people they are better off with lower wages remains a tough sell among wage earners. The continued popularity of a higher minimum wage suggests there are many that work for wages who understand employers and employees have opposite economic interests. Employees outnumber employers by enough to expect a raise, but politics is a messy business. Will Congress go with the numbers?
[1] David Neumark and William L. Wascher, Minimum Wages, (Cambridge, MA: The MIT Press, 2008), 295 pages.
[2] U. S. Bureau of Labor Statistics, Occupational Employment Survey
At $9.00 an hour per full time employee the increase converts $3,640 [$1.75 x 2,080] of profit to cost per full time minimum wage employee. To employers of low wage jobs like ushers, lobby attendants, ticket takers, shampooers, or child care workers higher wage costs bring pressure to experiment with higher prices, and fewer work hours or jobs. Raising prices might raise revenue and restore profits as long as sales don’t fall by much. Otherwise cutting jobs or hours in response to a higher minimum wage should help restore profits.
Since everyone agrees higher wages do pressure employers to cut work hours or jobs for employees paid below the minimum wage that part makes for easy agreement. However, it represents a small part of the minimum wage debate, unless economists and their business clients expect job losers to disappear, never to work again.
In their book Minimum Wages economists David Neumark and William L. Wascher write on page 116, “. . . as we emphasized earlier in this chapter the potential for minimum wage increases to affect wages higher in the wage distribution is also important in assessing the effects of minimum wage policy.” (1)
When the minimum wage jumped by $2.10 an hour from 2006 to 2009, jobs as fast food cooks dropped from 612 thousand to 539 thousand. (2) During the same period there were other jobs as cashiers, retail salespersons, rental and counter clerks and others with wage ranges above the minimum. An increase in applications for these other jobs quite likely holds down wages as economists like to predict from any increase in supply, but in wage ranges above the minimum. As people find other jobs in other industries and occupations the higher minimum wage can work to increase employment at higher wages.
In spite of their conclusions, Neumark and Wascher “. . . find it very difficult to see good economic rationale for continuing to seek a higher minimum wage.” In this they are like all economists who have been reciting conclusions like that for decades. Telling people they are worse off with a higher wage makes it necessary to quickly convince the public that jobs will be lost.
Neumark and Wascher and other economists try to convince people by theorizing in the specialized terminology of the economics fraternity. At page 254 they write “In the model, an increase in the nominal wage that raises the wage rate of unskilled labor not only induces substitution of skilled for unskilled labor, it also leads to substitution of unionized skilled labor for non-unionized skilled labor because the union sector expands and the nonunion sector contracts.” Their predictions come without mention of occupations like cashier, clerk or fast food cook and lead to conclusions applied to generic markets of products and jobs. The authors might recognize the millions of opportunities to move from low wage to higher wage employment by looking at wage distributions by occupation reported by the U. S. Bureau of Labor Statistics in their Occupational Employment Survey.
Business predictably opposes a higher minimum wage year after year. For individual business a higher minimum wage always converts profits to costs, even though the economy needs people with income to put back in the spending stream. Economists repeatedly offer theoretical support as though they are paid spokesmen or women.
Telling people they are better off with lower wages remains a tough sell among wage earners. The continued popularity of a higher minimum wage suggests there are many that work for wages who understand employers and employees have opposite economic interests. Employees outnumber employers by enough to expect a raise, but politics is a messy business. Will Congress go with the numbers?
[1] David Neumark and William L. Wascher, Minimum Wages, (Cambridge, MA: The MIT Press, 2008), 295 pages.
[2] U. S. Bureau of Labor Statistics, Occupational Employment Survey
Monday, April 15, 2013
Minimum Wages - A Review
David Neumark and William L. Wascher, Minimum Wages, (Cambridge, MA: The MIT Press, 2008), 295 pages.
The two economist authors wrote Minimum Wages for economists; that is except for a couple of sentences in the last chapter. The title of the last chapter, Summary and Conclusions, signals politicians and business types to the pages where they will find the conclusions they want to hear: “Based on the evidence from our nearly two decades of research on minimum wages . . . we find it very difficult to see good economic rationale for continuing to seek a higher minimum wage.”
Chapter two has the history and law of minimum wages and there are chapters describing changes on employment, wage distribution, income distribution, prices, profits and training incentives. A political economy of minimum wages chapter precedes the summary.
Chapter three has 70 pages reviewing 43 studies of the minimum wage effects of a higher minimum wage on employment. The summary reviews come after a section titled the neoclassical model where the authors narrate a description of the “textbook” neoclassical model in its “simplest” form. It assumes competition for labor and product markets, one type of labor, output produced with a mix of capital and labor, and minimum wage coverage for all. A minimum wage above the market wage creates two causes for declining employment. First, it raises establishment costs and market prices that cause falling product demand and ultimately falling employment. Second it raises wages leading to a substitution of capital for labor.
Paragraphs that begin with extensions of the model add or change selected assumptions. In one extension, minimum wages can be covered or uncovered. In a second, labor can be skilled or unskilled. In the first extension the authors assert “. . . the uncovered sector may provide alternative opportunities to workers who cannot finds jobs in the covered sector and thus can potentially mitigate the overall employment losses associated with the minimum wage.”
In the second extension the authors assert “. . . the neoclassical model’s prediction of a reduction in labor demand applies unambiguously only to less-skilled workers whose wages are directly raised by the minimum wage. The effects on other workers depend on the nature of the production process and, indeed, the minimum wage can generally be expected to lead to an increase in the employment of slightly higher-skilled workers who are good substitutes for minimum wage workers.”
To employers of dishwashers, ushers, lobby attendants, ticket takers, shampooers, and child care workers higher wage costs reduce profits pressuring employers to experiment with higher prices, and fewer work hours or jobs. Raising prices might raise revenue and restore profits as long as sales don’t fall by much. Otherwise cutting jobs or hours in response to a higher minimum wage should help restore profits. Since everyone agrees higher wages do pressure employers to cut work hours or jobs for sub-minimum wage employees that part makes for easy agreement. However, it represents a small part of minimum wage policy, unless the authors expect job losers to disappear, never to work again.
The authors do worry about what else happens after low wage employees lose their jobs. Repeatedly they pose different options with new assumptions and another chain of deductive model building. On page 50 they write under an assumption of partial minimum wage coverage “. . . the minimum wage raises the supply of labor to the uncovered sector, which lowers the wage and increases employment in that sector, thus offsetting some of the job loss in the covered sector.” Again in similar fashion on page 116, “. . . as we emphasized earlier in this chapter the potential for minimum wage increases to affect wages higher in the wage distribution is also important in assessing the effects of minimum wage policy.”
Both of these citations from the authors contradict their conclusion that a higher minimum wage necessarily harms employment. They agree if people lose their minimum wage job they do not disappear, but begin looking for other jobs in other occupations with wages higher in the wage distribution. Forced to leave a sub-minimum wage job the newly unemployed increase the supply of labor in other occupations where they moderate higher wages and add to employment. The authors might recognize the millions of opportunities to move from low wage to higher wage employment by looking at wage distributions by occupation reported by the U. S. Bureau of Labor Statistics in their Occupational Employment Survey.
Obsessive model building quickly turns the book into a tedious slog through neoclassical constructs in the specialized terminology of the economics fraternity. The authors use characterizations for model building like covered and uncovered, skilled and unskilled, union and non-union without mention of occupations like lawyer, engineer, clerk or cashier.
Many times the authors describe models that bring a “substitution of skilled for unskilled labor,” and vice versa. At page 254 readers find “In the model, an increase in the nominal wage that raises the wage rate of unskilled labor not only induces substitution of skilled for unskilled labor, it also leads to substitution of unionized skilled labor for non-unionized skilled labor because the union sector expands and the nonunion sector contracts.” Most people think of lawyers and engineers as skilled labor and clerks and cashiers as unskilled labor but not substitutes. Substitutes have characteristics similar enough to be interchangeable, but the authors repeatedly treat substitutes as different enough to be in separate markets.
A succession of models and assertions lead to conclusions of up, down, higher, lower applied to generic markets of products and jobs. The authors report regression estimates with tables of numerical coefficients, but these estimates came from aggregated data of many occupations and markets. Aggregated data doesn’t tell us what happens to fast food cooks after a minimum wage increase.
When the minimum wage jumped by $2.10 an hour from 2006 to 2009, jobs as fast food cooks dropped from 612 thousand to 539 thousand. During the same period there were jobs as cashiers, retail salespersons, rental and counter clerks and others with wage ranges above the minimum. An increase in applications for these other jobs quite likely holds down wages as economists like to predict from any increase in supply, but quite possibly in wage ranges above the minimum. A higher minimum wage might work out to higher employment, higher wages and lower wage inequality.
In the policy chapter the authors suggest some special interest groups support a higher wage because it helps them. Others who support raising the minimum wage are confused or uninformed; not clued into the power of neoclassical market forecasts. Economists have been reciting these conclusions for decades, but if you are a stickler for details and want to know how to support that view, you will not find it in this book. If you always want to oppose a higher minimum wage, do as the authors do, say it’s a bad thing that hurts employment.
The two economist authors wrote Minimum Wages for economists; that is except for a couple of sentences in the last chapter. The title of the last chapter, Summary and Conclusions, signals politicians and business types to the pages where they will find the conclusions they want to hear: “Based on the evidence from our nearly two decades of research on minimum wages . . . we find it very difficult to see good economic rationale for continuing to seek a higher minimum wage.”
Chapter two has the history and law of minimum wages and there are chapters describing changes on employment, wage distribution, income distribution, prices, profits and training incentives. A political economy of minimum wages chapter precedes the summary.
Chapter three has 70 pages reviewing 43 studies of the minimum wage effects of a higher minimum wage on employment. The summary reviews come after a section titled the neoclassical model where the authors narrate a description of the “textbook” neoclassical model in its “simplest” form. It assumes competition for labor and product markets, one type of labor, output produced with a mix of capital and labor, and minimum wage coverage for all. A minimum wage above the market wage creates two causes for declining employment. First, it raises establishment costs and market prices that cause falling product demand and ultimately falling employment. Second it raises wages leading to a substitution of capital for labor.
Paragraphs that begin with extensions of the model add or change selected assumptions. In one extension, minimum wages can be covered or uncovered. In a second, labor can be skilled or unskilled. In the first extension the authors assert “. . . the uncovered sector may provide alternative opportunities to workers who cannot finds jobs in the covered sector and thus can potentially mitigate the overall employment losses associated with the minimum wage.”
In the second extension the authors assert “. . . the neoclassical model’s prediction of a reduction in labor demand applies unambiguously only to less-skilled workers whose wages are directly raised by the minimum wage. The effects on other workers depend on the nature of the production process and, indeed, the minimum wage can generally be expected to lead to an increase in the employment of slightly higher-skilled workers who are good substitutes for minimum wage workers.”
To employers of dishwashers, ushers, lobby attendants, ticket takers, shampooers, and child care workers higher wage costs reduce profits pressuring employers to experiment with higher prices, and fewer work hours or jobs. Raising prices might raise revenue and restore profits as long as sales don’t fall by much. Otherwise cutting jobs or hours in response to a higher minimum wage should help restore profits. Since everyone agrees higher wages do pressure employers to cut work hours or jobs for sub-minimum wage employees that part makes for easy agreement. However, it represents a small part of minimum wage policy, unless the authors expect job losers to disappear, never to work again.
The authors do worry about what else happens after low wage employees lose their jobs. Repeatedly they pose different options with new assumptions and another chain of deductive model building. On page 50 they write under an assumption of partial minimum wage coverage “. . . the minimum wage raises the supply of labor to the uncovered sector, which lowers the wage and increases employment in that sector, thus offsetting some of the job loss in the covered sector.” Again in similar fashion on page 116, “. . . as we emphasized earlier in this chapter the potential for minimum wage increases to affect wages higher in the wage distribution is also important in assessing the effects of minimum wage policy.”
Both of these citations from the authors contradict their conclusion that a higher minimum wage necessarily harms employment. They agree if people lose their minimum wage job they do not disappear, but begin looking for other jobs in other occupations with wages higher in the wage distribution. Forced to leave a sub-minimum wage job the newly unemployed increase the supply of labor in other occupations where they moderate higher wages and add to employment. The authors might recognize the millions of opportunities to move from low wage to higher wage employment by looking at wage distributions by occupation reported by the U. S. Bureau of Labor Statistics in their Occupational Employment Survey.
Obsessive model building quickly turns the book into a tedious slog through neoclassical constructs in the specialized terminology of the economics fraternity. The authors use characterizations for model building like covered and uncovered, skilled and unskilled, union and non-union without mention of occupations like lawyer, engineer, clerk or cashier.
Many times the authors describe models that bring a “substitution of skilled for unskilled labor,” and vice versa. At page 254 readers find “In the model, an increase in the nominal wage that raises the wage rate of unskilled labor not only induces substitution of skilled for unskilled labor, it also leads to substitution of unionized skilled labor for non-unionized skilled labor because the union sector expands and the nonunion sector contracts.” Most people think of lawyers and engineers as skilled labor and clerks and cashiers as unskilled labor but not substitutes. Substitutes have characteristics similar enough to be interchangeable, but the authors repeatedly treat substitutes as different enough to be in separate markets.
A succession of models and assertions lead to conclusions of up, down, higher, lower applied to generic markets of products and jobs. The authors report regression estimates with tables of numerical coefficients, but these estimates came from aggregated data of many occupations and markets. Aggregated data doesn’t tell us what happens to fast food cooks after a minimum wage increase.
When the minimum wage jumped by $2.10 an hour from 2006 to 2009, jobs as fast food cooks dropped from 612 thousand to 539 thousand. During the same period there were jobs as cashiers, retail salespersons, rental and counter clerks and others with wage ranges above the minimum. An increase in applications for these other jobs quite likely holds down wages as economists like to predict from any increase in supply, but quite possibly in wage ranges above the minimum. A higher minimum wage might work out to higher employment, higher wages and lower wage inequality.
In the policy chapter the authors suggest some special interest groups support a higher wage because it helps them. Others who support raising the minimum wage are confused or uninformed; not clued into the power of neoclassical market forecasts. Economists have been reciting these conclusions for decades, but if you are a stickler for details and want to know how to support that view, you will not find it in this book. If you always want to oppose a higher minimum wage, do as the authors do, say it’s a bad thing that hurts employment.
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