Some people don’t understand why organic farming isn’t more popular than it is
20 Dec 2014 Leave a comment
in applied price theory, entrepreneurship, health economics, rentseeking Tags: organic farming, Quacks
The rise of the working rich among the top 0.1% in the USA
19 Dec 2014 Leave a comment
in applied welfare economics, economic history, entrepreneurship, politics - USA, poverty and inequality
Source: “Income Inequality in the United States, 1913-1998” with Thomas Piketty, Quarterly Journal of Economics, 118(1), 2003, 1-39
(Tables and Figures Updated to 2012 in Excel format, September 2013) via Chad Jones
Before 1940, most of the income of the top 0.1% of income earners in the USA was income from investments.
By the end of the 20th century, the top 0.1% were earning their incomes as wages and salaries, business incomes and capital gains. Very little of that income of the top 0.1% was in the form of passive income from capital. The top 0.1% of the USA are now working rich – entrepreneurs.
The slow diffusion of modern human resource management
19 Dec 2014 Leave a comment
in entrepreneurship, human capital, industrial organisation, managerial economics, market efficiency, organisational economics, personnel economics, survivor principle Tags: firm size, modern human resource management, technology diffusion, The meaning of competition
Modern human resource management gained ground in the 1980s, slowly replaced the centralising of people management in personnel departments that was widespread by the 1960s.
Modern human resource management stressed rigorous selection and recruitment, more training at induction and on-the-job, more teamwork and multi-skilling, better management-worker communication, the use of quality circles, and encouraging employee suggestions and innovation.
The aim is a highly committed and capable workforce that pulls toward common goals. This drive for employer-employee unity is in contrast to the old days of detachment and formality with managers directing and controlling workers.
Modern human resource management replaced compliance with rules with genuine employee commitment and a unified corporate culture.
Modern human resource management is a technology and there is a long lag on the widespread adoption of any new technology.
The lag on the intra-industry diffusion of new technologies from 10% to 90% of users is 15 to 30 years long (Hall 2003; Grubler 1991). The literature on technology transfer is full of examples of the slow and costly diffusion of new technologies even with the on-site help of the original innovator and experienced consultants (Boldrin and Levine 2008).
New management practices are often complex and they are often slow and costly to introduce successfully without the assistance of consultants with prior experience with the new practices (Bloom and Van Reenen 2007, 2010).
Managerial innovations such as Taylor’s scientific management, Ford’s mass production, Sloan’s M-form corporations, Deming’s quality movement and Toyota’s lean manufacturing diffused slowly over decades. These technologies required large investments in learning, retraining, reorganisation, trial and error and adaptation and there were many failures (Bloom and Van Reenen 2010).
Bryson, Gomez, Kretschmer and Willman (2007) found that workplace voice and modern, high-commitment human resource management practices diffused unevenly across British workplaces. More employees, larger multi-establishment networks, public or for-profit ownership and network effects all increased the rates of diffusion of the new practices.
Large firms may invest more in skills because they are the early adopters of new management practices. Large firms are organisationally complex and they require more structured, explicit management practices to survive. Higher levels of worker skills have been linked with firms having better management practices (Bloom and Van Reenen 2007, 2010).
Employers who pay higher wages lose more if they mismanage or under-utilise well-paid workers. Large firms pay more, on average, so they lose more if they do not adopt good management practices in a timely fashion.
There are fixed costs to adopting new technologies and management practices, so large firms may be the first to find them profitable (Hall 2003). Later adopters may follow this lead when the new practices are more proven and, through experience and adaptation, cheaper to adopt.
The organisational disruption from switching to any new technology can reduce production and profits for several years and the new way of doing business may fail perhaps at a great cost (Holmes, Levine, and Schmitz 2012; Atkeson and Kehoe 2007; Roberts 2004).
These costs and uncertainties slow technology diffusion and explain why smaller firms use seemly out-of-date management practices. The new ways are not yet profitable for them. The pace of adoption of new technologies is driven by changes in the profitability of using the new technology as compared to the old (Karshenas and Stoneman 1993).
Firms of different sizes will invest in skills development and new management practices to the extent that is profitable to their circumstances.
On some occasions, large firms will find it profitable to invest in more skills development because this is part of the costs of investing in more capital per worker. On other occasions, skills development is necessary to reduce the costs of a growing corporate hierarchy.
No firm cannot invest in more skills development unless this growth is buoyed by market demand. Precipitate investments in skills development are fraught with risks.
The role of news in real business cycles
18 Dec 2014 Leave a comment
in business cycles, economic growth, entrepreneurship, job search and matching, macroeconomics Tags: real business cycles
Revisions in investor beliefs about productivity prospects can partly account for business expansions and contractions. If favourable news about future technological opportunities can seed a boom today in consumption and investment before the actual technological improvement arrives and is realised, news that future productivity growth may not be as good as was previously expected can induce a recession without any actual change in productivity ever occurring.
Investors build in anticipation, starting new projects and recruiting more staff. Their forecasts can turn out to be too optimistic. When entrepreneurial expectations of future productivity are revised, investment demand can fall because of an excess in capital accumulation – recent investments were made under more optimistic beliefs about productivity (Beaudry and Portier 2004).
Investment demand must be muted for a time until the excess capital accumulation is brought into use, refitted or scraped. There also will be layoffs and a lull in recruitment. Job search strategies must also change as job seekers redirect their careers in light of the news about their revised prospects in different firms, industries and competing occupations.
The optimism and pessimism of investors are rational profit-seeking responses to new entrepreneurial knowledge. Profit expectations reflect consumer preferences, resource constraints and technological factors as they exist and are forecast to change and actual and forecasted opportunities and constraints in the investment sector. Entrepreneurs are dynamic risk takers who profit from anticipating shifts in consumer demand, input costs and technology.
Recessions and booms can arise due to the challenges facing entrepreneurs in forecasting the uncertain and ever-changing future demand for new capital that is implied by their forecasts of consumer demand and technological opportunities as Beaudry and Portier (2004) explain:
The view that recession and booms may arise as the result of investment swings generated by agents’ difficulties to properly forecast the economy’s need in terms of capital has a long tradition in economics.
For example, this difficulty was seen by Pigou as being an inherent feature of any economy with technological progress.
As emphasized in Pigou (1926), when agents are optimistic about the future and decide to build up capital in expectation of future demand then, in the case where their expectations are not met, there will be a period of retrenched investment which is likely to cause a recession.
Revisions in entrepreneurial beliefs and investment plans can be required when new information is uncovered (Beaudry and Portier 2004; Sill 2009). There can be lulls in investment demand following these revisions to entrepreneurial forecasts leading to recessions. As Pigou noted in 1927:
The varying expectations of business men … constitute the immediate cause and direct causes or antecedents of industrial fluctuations
The Wealth of Grumpy Cat – In defense of the monetisation of uncommon cuteness.
18 Dec 2014 Leave a comment
in cats, economics of media and culture, entrepreneurship Tags: cats. grumpy cat
Robert Lucas and where have all the small entrepreneurs gone?
18 Dec 2014 1 Comment
in applied welfare economics, economics of regulation, entrepreneurship, industrial organisation, Robert E. Lucas, survivor principle, theory of the firm Tags: entrepreneurship, firm entry, firm exit, occupational choice
Robert Lucas predicted the decline in the number of small business people and small firms in 1978. The number of small firms will fall and the number of large firms will rise with increases in real wages (Lucas 1978; Poschke 2013; Gollin 2008; Eeckhout and Jovanovic 2012).
Lucas closed his 1978 discussion of the size distribution of firms, and how firms are getting larger an average over the course of the 20th century, with a discussion of a lovely restaurant he visited on the Canadian border. He predicted that in couple of decades time, these type of restaurants will be fewer.
Nations that are more productive over time and have higher wages because they have accumulated more capital per worker.
One consequence of more capital per worker is real wages increase at a faster rate than profits (Gollin 2008; Eeckhout and Jovanovic 2012). For example, the rate of return on capital was stable over the 20th century while real wages increased many fold (Jones and Romer 2010). This relationship turns out to be crucial in terms of occupational choice and the decision to become an entrepreneur – a small business owner
Higher wages reduces the supply of entrepreneurs and increases the average size of firms because entrepreneurship becomes a less attractive occupational choice (Lucas 1978; Gollin 2008; Eeckhout and Jovanovic 2012).
For example, in the mid-20th century, many graduates who were not teachers were self-employed professionals. With an expanding division of labour because of economic growth, many well-paid jobs and new occupations emerged for talented people in white-collar employment.
OECD countries richer than New Zealand should have less self-employment and more firms that are large because paid employment is an increasingly better-rewarded career option for their high skilled workers.
The U.S. had the second lowest share of self-employed workers (7 per cent) in the OECD in 2010 – the latest data – which is less than half the rate of New Zealand self-employment (16.5 per cent) in 2011 (OECD 2013). The Australian self-employment rate was 11.6 per cent in 2010 (OECD 2013).
A companion reason for larger average firm sizes in countries richer than New Zealand is more capital-intensive production can prosper in larger corporate hierarchies than can labour-intensive production (Lucas 1978; Becker and Murphy 1992; Poschke 2011; Eeckhout and Jovanovic 2012).
The more able entrepreneurs can run larger firms with bigger spans of control in richer countries because their employees can profitably use more capital per worker with less supervision. The diseconomies of scale to management and entrepreneurship should rise at a faster rate in less technological advanced countries such as New Zealand because they are more labour intensive economies (Lucas 1978; Becker and Murphy 1992; Poschke 2011; Eeckhout and Jovanovic 2012).
Importantly, the more able entrepreneurs benefit most from introducing frontier technologies because they can deal more easily with their increased complexity and more uncertain prospects (Poschke 2011; Lazear 2005; Shultz 1975; 1980). Growing technological complexity reduces the supply of entrepreneurs because it takes longer to acquire the necessary balance of skills and experience needed to lead a firm (Lazear 2005; Otani 1996).
The more marginal entrepreneurs will switch to be employees as technology advances so the average size of firms will increase. The entrepreneurs that remain in business will be the most able, more skilled and more experienced entrepreneurs and will be more capable of running larger firms that pioneer complex, frontier technologies (Poschke 2011; Lazear 2005, Otani 1996; Lucas 1978).
Countries more technologically advanced than New Zealand will have both larger firms and less self-employment because of growing technological complexity.
The greater is the exposure to foreign competition, the smaller is the fraction of self-employed and small firms in a country (Melitz 2003; Díez and Ozdagli 2012). More foreign competition increases wages because of lower prices, which makes self-employment less lucrative. More exporting favours larger firms both because of the fixed costs of entering export markets and because the stiffer competition will weed-out the lower ability entrepreneurs who run the smaller firms (Melitz 2003; Díez and Ozdagli 2012).
Other factors can countermand the effects that occupational choice, frontier technologies, exporting and capital intensity have to increase the average size of firms as real wages rise.
For example, tax and regulatory policies reduce the average size of firms in many EU member states to levels that are similar to New Zealand. The EU is less likely to have large firms in its labour intensive sectors. Employment protection laws, product market and land use regulation and in particular, high taxes stifled the growth of labour intensive services sectors in the continental EU (Bertrand and Kramatz 2002; Bassanini, Nunziata and Venn 2009; Rogerson 2008).
EU firms are are more capital intensive with fewer employees than otherwise because labour is so expensive to hire in the EU. Small and medium sized firms can struggle to grow in much of the EU because of regulatory burdens that phase in with firm size (Garicano, Lelarge and Van Reenen 2012; Hobijn and Sahin 2013; Rubini, Desmet, Piguillem and Crespo 2012). Average firm sizes are 40% smaller in Spain and Italy than in Germany. Obstacles to firm growth originate in product, labour, technology and financial and the binding constraints differ from one EU member state to another (Rubini, Desmet, Piguillem and Crespo 2012).
Average firm sizes in the USA and UK may be larger because of fewer tax and regulatory policies that limit business growth. Bartelsman, Scarpetta and Schivardi (2005) found that new entrants in the U.S. started on a smaller scale than in Europe but grew at a much higher rate. This willingness to experiment on a smaller scale was worth the risk because the payoff was much larger in terms of growth in the more flexible U.S. markets.
In summary, many factors drive the size distribution of firms countries including taxation and regulation. Underlying this, nonetheless, is Lucas’s point from 1978 that rising real wages makes starting a small business a less inviting occupation choice.
Was Aaron Sorkin right? Hollywood discriminates? Sacrifices profit to indulge sexism?
17 Dec 2014 1 Comment
Real business cycles and learning the value of major technological changes
17 Dec 2014 Leave a comment
in business cycles, entrepreneurship, macroeconomics, technological progress Tags: boom and bust, general purpose technologies, real business cycles
The true value of any technological improvement is uncertain. Investors adopt a new technology after forecasting the likely productivity of the new technology. Investor learning in the face of imperfect information about the true value of major new technologies can also lead to business cycle fluctuations (Li 2007).
As a new technology slowly diffuses, entrepreneurs learn more about the true potential of the new technology and re-evaluate in hindsight whether they have invested beyond the optimal amount. If entrepreneurs have not over-invested, they revise their beliefs about the magnitude of the innovation and invest more.
Because the agents have to learn the magnitude of the technology shock, they are cautious in making investment decisions before they have learned much about the underlying technology. Consequently, GDP growth is gradual, which stretches out the length of booms.
When entrepreneurs later find that investment has over-shot the optimal amount, they reduce investment demand perhaps sharply and start a recession (Li 2007). This eventuality may seed a recession within many major technology advances such as the IT boom in the 1990s and the computer revolution in the 1970s.
The true value of the major technological improvement is often discovered only after investment over-shoots the optimal level (Li 2007). A general technological innovation affecting many industries is required for the cluster of entrepreneurial errors about the true magnitude of the productivity increase to seed a recession (Li 2007).
The 2001 US recession followed a long boom involving major new information and communication technologies that raised the productivity of many existing technologies. The information, communications and software boom lasted over a decade in the US (Li 2007).
Entrepreneurs invested gradually in new information and communication capital to learn more about the underlying technologies that they embodied. These new information and communication technologies were productivity improvements of a major but uncertain scope (Li 2007).
The eventual productivity gains come from two complex sources – both from adopting the new technology itself and from its interface with existing capital and expertise. Because both productivity gains must be forecasted and because both are discovered only by experimentation and learning by doing, it is entirely possible that entrepreneurs can invest ahead of consumer demand.
This surplus capacity will emerge despite the best efforts of investors to mitigate this risk by staggering investments to learn more about the true value of the new technology. This investor caution and staggering to allow for more learning is an important factor that stretches out the length of investment booms in major new technologies (Li 2007).
There was a sharp decline in US investment in 2001, with large accumulations of unused capital in some sectors. For example, 90% of the optical fibre laid in the US in the 1990s was unused in the years that followed. Entrepreneurs discovered the optimum investment level in, for example, optical cable fibre by investing past it and revised plans for further investments in light of this over-shooting (Li 2007).
Real business cycles of a significant magnitude can emerge simply from technological learning.
Li (2007) argued that many investment booms start with the advent of a revolutionary technology and ended with overinvestment. For example, canal building boomed after the invention of the steamboat, and by the year 1860 more than 4,000 miles of canal had been completed. However, many of these canals did not live up to the expectations of their promoters. Many of these projects eventually turned out to be financial failures.
Later in the same century, the railroad expansion shared a similar fate. Thousands of miles of railroad were built and left unused or under used, a phenomenon described by Schumpeter (1949) as construction “ahead of demand.”
That real business cycle theory required technological regress for there to be recessions is one of its oldest criticisms. That criticism that standard equilibrium business cycle models have difficulties in predicting the investment boom and overshooting grows weaker by the day.
Li presents a strong internal propagation mechanism with respect to technology shocks and endogenous recessions without invoking technological regress:
…firms invest in new capital to take advantage of the IT revolution, without knowing the limit to which this new technology can increase productivity.
The belief of this limit becomes increasingly optimistic over time as investors repeatedly realize that they have not invested enough to exhaust the potential of the new technology. Such belief revisions lead to increasingly aggressive investment and a capital overhang, followed by a recession.
Why are we always restructuring the workplace? The economics of organisational fickleness
16 Dec 2014 2 Comments
in entrepreneurship, industrial organisation, managerial economics, market efficiency, organisational economics, personnel economics, survivor principle Tags: industrial organisation, survivior principle
Ok, whatever is, is efficient, but I always had my doubts when we are always restructuring wherever I worked. This continual organisational upheaval and restructuring was also a phenomena in the private sector.
What was the survival value of this continual disruption of organisational form and organisational capital in competition with rival firms with more stable internal organisational forms?
Internal reorganisations divert management time away from more profitable pursuits such as facilitating production. Managerial resources are scarce, like any other resource, and must be allocated to their highest value uses.
But as a firm grows, waste accumulates through the duplication of employee effort and the assignment of unnecessary tasks within the organisation.
Jack Nickerson and Todd Zenger wrote a great paper in 2002 on the efficiency of being fickle – of repeated reorganisations of the workplace. Their point was simple: times change and they change a lot faster than we think so organisations have to adapt to their rapidly unfolding new market conditions.
They illustrated their point about the need for regular reorganisation inside a short period of time with a case study of the alternating waves of centralisation and decentralisation in Hewlett-Packard.
Throughout the 1970s, Hewlett-Packard was a thoroughly decentralised organisation and was successful in the market. It had a remarkable record of innovation in the 1970s.
In the early 1980s, Hewlett-Packard hard found this decentralisation was starting to work against it in the rapidly evolving computer market. The Independent divisions developed computers, peripherals and components that will both incompatible with each other and competed with each other.
This redundancy between the independent divisions was costly and was confusing to consumers because they had a hodgepodge of products that really won’t related to each other. The computer industry in the early 1980s was involving very rapidly with many incompatible computers and programs, but the few that turned out to be the best became immensely profitable.
In 1984 and 1985, Hewlett-Packard hard centralise product development in headquarters and put all marketing and sales into one unit. Financial performance recovered after this reorganisation.
By 1990, Hewlett-Packard was on again in a steep financial decline. The centralisation of decision-making has slowed product development and there was a significant drop in innovation.
In 1990, computers was separated into competing products and computing systems. Individual product lines were decentralised and treated a separate business units.
In 1994, Hewlett-Packard again decentralised customer support of all computer activities. Three years later, it decentralised the same activities into three organisations. In 1999 it spun off its instruments and medical business.
Over 16 years, Hewlett-Packard, experience five fundamental ships alternating between decentralisation and centralisation. Each one of these reorganisations was greeted with the share price increase.
The reason why this fickleness in organisational form was efficient was the market changes rapidly. Organisational forms and organisational capital become obsolete rather quickly.
The form of organisation that survives in competition with actual and potential market rivals is that specific form of organisation which allows the firm to deliver the products that customers want at the lowest price while covering costs (Alchian 1950; Fama and Jensen 1983a, 1983b).
Each time Hewlett-Packard decentralised was a time in the product life cycle of their industry where there was rapid innovation. Hewlett-Packard tended to centralise in the consolidation phase of product life cycles.
New technologies are unproven and they come with much less information and prior experience to guide the top of a hierarchy in directing their successful adoption from a distance (Acemoglu, Aghion, Lelarge, Van Reenen and Zilibotti 2007). In any hierarchy, the top faces two problems with their subordinates: communicating their desires and seeing that they are carried out (Tullock 2005).
When a large firm directs major changes from the top of a hierarchy, failures of communication in the chain of command are a growing risk. More employees require more supervisors. More supervisors require more supervisors of supervisors at every tier of the hierarchy – the layers of supervision multiply (Posner 2010; Williamson 1975, 1985).
There are delay in executing orders, a loss of information and feedback on the way up, and the truncation of the directions from the top: there is a general weakening of control and coherence (Posner 2010; Williamson 1975, 1985). The daily implementation problems of new technologies cannot go up and down a hierarchy for resolution.
Firms must decentralise (rather than grow in hierarchy) to profit most from a line manager’s superior local knowledge about the implementation of the latest, more complex technologies. Delegating initiative to managers downstream is vital when a large firm introduces frontier technologies about which information flows upstream are slow and considerable learning by doing and rapid adaptation are required (Acemoglu, Aghion, Lelarge, Van Reenen and Zilibotti 2007; Jensen and Meckling 1995).
New technologies usually bug-ridden and require considerable refinement, adaptation and consumer feedback on their use before the mature product emerges (Greenwood 1999; Greenwood and Yorukoglu 1997). This costly process of learning, improvisation and product and process re-design explains the multi-decade long 10-90 lag in technology diffusion across firms in the same industry and the slow rate of consumer acceptance of new products.
Larger firms may struggle with striking the most profitable balance between greater local managerial discretion and effective corporate governance of a large diverse organisation with professional managers and diffuse ownership structures.
A risk of greater local managerial discretion in a large firm is less effective governance (Williamson 1975, 1985; Fama and Jensen 1983a, 1983b). The risks of separating of ownership from control and the distortions to knowledge flows in hierarchies drives the internal organisation of large firms and the division of decision control and decision management rights between the board and management (Fama and Jensen 1983a, 1983b; Williamson 1985).
The separation of decision management rights, vested in hired managers, from decision control rights, vested in the board of directors, is a common governance safeguard against conflicts of interest in business, professional and non-profit organisations, large and small (Fama and Jensen 1983a, 1983b).
Decision management rights cover the initiation and the implementation of decisions. Decision control rights involve the ratification and the monitoring of decisions. Managers and division heads carry out the production decisions, budgets and policies on wages, hours, staffing and job designs developed by head office and which are ratified by the board of directors (Fama and Jensen 1983b, 1985).
Competition between different sizes, shapes and internal organisational forms of firms all vying for sales, cheaper sources of supply and investor support sifts out the keener priced, lower cost, and more innovative enterprises (Alchian 1950; Stigler 1958). These lower-cost firms will be able to under-sell their higher cost rivals.
The winning firm size and internal organisational shape is that configuration which meets any and all problems the firm is actually facing and seizes more of the entrepreneurial opportunities that are within its grasp (Stigler 1958; Alchian 1950).
Large firms invest heavily in mimicking the nimbleness of small firms. Some firms re-create some of the advantages of being small by organising into M-form hierarchies made up of product divisions to improve performance monitoring, identify managerial slack, encourage mutual monitoring, promote competition within the firm for top-level management positions and facilitate comparisons of compliance with the policies of head office (Klein 1999; Fama and Jensen 1983a, 1983b; Williamson 1975, 1985).
Large firms must develop organisational architectures to assign decision rights, reward employees, and evaluate the performance of employees and business units. The aim is to empower subordinates with the requisite local knowledge with the power to act swiftly and the incentive to make good decisions. The organisational architecture of a firm encompasses the assignment of decision rights within the firm, the methods of rewarding individual employees, and the structure of the systems that evaluate the performance of individual employees and business units.
Poor cost control, budgetary excess and any lack of innovation and initiative over products designs and pricing, input mixes and wage and employment policies will reflect in relative divisional performances and overall corporate profits.
Any news of less promising current and future net cash flows will feed into share prices and into the labour market prospects of both career managers and the members of boards of directors (Manne 1965; Jensen and Meckling 1976; Fama and Jensen 1983a, 1983b; Demsetz 1983; Demsetz and Lehn 1985). To survive, managerial firms must balance delegation with more centralised control (Fama and Jensen 1983a; McKenzie and Lee 1998).
One way of balancing delegation with centralised control is simply to reorganise the firm on a regular basis as market circumstances change and entrepreneurial judgements about the future are updated. This regular reorganisation of the firm may seem fickle, but the firm must adapt or die. Firms must be efficiently fickle in their organisational forms.
Not only is whatever is, is efficient, any attempt to change whatever is, is efficient, because otherwise it wouldn’t be attempted. Of course, these reorganisations are entrepreneurial ventures that are never guaranteed success.
Entrepreneurship and sectoral mismatches in labour supply and labour demand
15 Dec 2014 1 Comment
in business cycles, entrepreneurship, job search and matching, macroeconomics Tags: business cycles, Fischer black, mismatch unemployment, sectoral unemployment
An important factor behind business fluctuations arises not from the balance between aggregate output and aggregate consumption, but from the accuracy of entrepreneurial matching of the individual patterns of output with the pattern of actual consumer demand in individual sectors (Black 1987, 1995).
Fluctuations in the match between resource deployment to different sectors and product demand across sectors can create major fluctuations in output and employment because moving resources from one sector into another is costly and time consuming.
What consumers will want and what can be produced in the future is uncertain. A plethora of sectors produce highly differentiated products with increasingly specialised inputs to serve consumers. Modern economic growth is built on ever greater product differentiation, ever greater product variety and ever increasing product quality produced by ever more specialised workers, firms and sectors. This explosion in specialisation is increasing the vulnerability of the business cycle to technology and taste shocks (Black 1987, 1995; Mehrling 2005).
Mismatches in the sectoral pattern of installed production capacity with actual consumer demand will arise because investments are driven by entrepreneurial forecasts of what will be wanted by consumers in the future. The capacity to produce output requires prior investments based on speculations about future consumer tastes, resource availabilities and technology progress. Part of the volatility in output and employment growth is from these investments depending on the uncertain details of the future.
Entrepreneurial errors in forecasting consumer wants will lead to inevitable mismatches of the production capacity with unfolding consumer demand. If future consumer tastes and upcoming technologies were better known now, employment would grow and be reallocated more smoothly to new uses than otherwise (Black 1987, 1995; Mehrling 2005).
When the match between forecasted and realised demand is good, there is a boom. Resources are where consumers want them. When the match is poorer, there is a recession. If events unfold in a markedly unanticipated direction, existing plans, investments and contracts require revision (Black 1987, 1995).
The existing matches between consumer desires, resource allocations by sector and production technologies can deteriorate. While a reallocation occurs, resources are diverted from production and are scrapped or are unemployed while searching for new uses (Black 1987, 1995).
Fixing a deteriorating match requires the structure of production to shift more into line with the structure of consumer demand. This takes time and consumes resources because human and other capital is highly specialised. It takes time for the new investments consistent with the latest entrepreneurial forecasts of consumer demand to be planned, built and start producing (Black 1987, 1995).
What can appear to be cyclical unemployment comes from alternations between periods of above and below average accuracy on entrepreneurial forecasting and better and worse matches in actual consumer demand and actual capacity to supply at the sector level (Black 1987, 1995; Mehrling 2005).
This type of cyclical unemployment is not a product of monetary, fiscal or other policy shocks. Resources need to be reallocated into a better alignment with consumer tastes and technological and resource possibilities. Preventing these sectoral reallocations will keep resources from moving from lower to higher value uses.
After longer booms, more human capital is more specialised to specific sectors, firms and jobs. This increased specialisation that helped underpin the prior economic boom can slow the recovery of employment at the end of the recession.
Job seekers will take longer to find good new job matches if they have more distinct backgrounds and specialised human capital. Job seekers have an incentive to search for longer to find these higher-paid job matches.
Employers will take longer to fill vacancies. The applicant pool is more diverse because of the high degree of specialisation of labour that is a legacy of the long prior boom. This accumulation of specific human capital over the course of longer booms will mean the length of the burden will affect the depth of the subsequent recession.More highly specialised workers have to be re-matched with new occupations and new sectors. More workers than usual will be putting off the day of having to face up to scrapping a significant part of their old human capital.
Utopia, you are standing in it! 
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