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The aim of the paper is to investigate Goodwin’s growth cycle in the Indian organised manufacturing industries.

The methodology is based on bi-variate differential equation, econometrics model like log-linear regression and Autoregressive Distributed Lag model. An empirical investigation is conducted on data from the Annual Survey of Industries from 1980 to 2018 time period.

The results indicate that though the original Goodwin model estimates deviated from data estimates, its modified (neo-Goodwin) model are found to be equivalent to the data estimates. Moreover, in contrast to the original model, the capital accumulation rate (investment to profit ratio) is not assumed to be unitary in the modified Goodwin model. Furthermore, the labour market-led and cost effect conditions of the Goodwin cycle are empirically verified by investigating the interdependency between employment rate and wage share. Lastly, the short- and long-run Goodwin cycles are observed to be moving in anti-clockwise direction in the employment rate and wage share bi-dimensional plane, thus confirming the existence of profit-led distribution where wage share continuously reducing with high employment.

This study opens the discussion on application of capitalistic model in the emerging economy and also suggests to incorporate some theoretical models like Kaldorian, Keynesian, Kaleckian or Schumpetrian into the Goodwin cycle.

This is the first paper which empirically examines the capitalistic nature of Indian organised manufacturing industries through the lens of Goodwin growth cycle and then extend it to the Neo-Goodwin model by relaxing one of the unrealistic assumption regarding unitary investment to profit ratio.

In recent years, with the gradual differentiation of economic and financial cycles, it has been increasingly difficult for monetary policies to remain balanced in stabilizing both economy and finance. Taking the period of 1999–2017 as a sample, the purpose of this paper is to find whether the synergy between the growth cycle and the price cycle is constantly improving in the economic cycle is more appropriate.

The key to stabilizing the economic cycle lies in the monetary policy and it should abandon the goal of boosting growth in a timely manner and turn into the goal of maintaining steady growth. At present, quantitative monetary policy is still more effective than price-oriented monetary policy in smoothing the economic cycle.

The impact of quantitative regulation on the financial cycle is more neutral, whereas price regulation will increase the volatility of price and financial cycles in the course of smoothing the growth cycle. In view of the continuous differentiation between the economic and financial cycles, it is realistic and reasonable to accelerate the establishment of a sound dual-pillar regulatory framework of “monetary policy and macro-prudential policy.”

The macro-prudential policy is specially used to smooth the financial cycle, so as to reduce the burden and increase the efficiency of the monetary policy on regulating economic cycle. Moreover, the transformation of monetary policy to price-oriented regulation must keep pace with the construction of the dual-pillar regulation framework and complement each other to prevent undesirable consequences in the financial sector. On the other hand, monetary policy still needs to rely on quantitative regulation in the future. The research in this paper also provides a new perspective for understanding the internal and external reform of China’s monetary policy in recent years.

This study aims to empirically examine the applicability of the life cycle model of firm performance to growth and profitability among Swedish small- and medium-sized enterprises (SMEs).

Using analysis of variance, multiple analysis of variance and three-stage least square modelling, this study analyses a longitudinal data set covering 26,721 Swedish SMEs in six industries from 2008 to 2011.

The empirical results indicate a clear life cycle performance pattern among the sampled SMEs, and that a six-stage life cycle model is applicable in predicting the performance pattern in terms of growth and profitability. On average, younger SMEs tend to display better performance in terms of growth and profitability than do their older and larger counterparts; moreover, larger SMEs tend to achieve better performance than do smaller ones.

The findings help SME managers understand how their decision-making style, strategy and structure can be related to various life cycle stages. Such an understanding may help them improve firm performance over time. Policymakers may find the results useful in coordinating SME support in line with various life cycle stages.

To the authors’ knowledge, this study is one of only a few using two performance variables to test the applicability of the life cycle model in a longitudinal and cross-industrial sample.

The purpose of this paper is to develop growth models that depart from the conventional framework, in the sense that consumption decisions take into account previous periods' expectations about output fluctuations. Households will raise their propensity to consume in periods of expected expansion and they will lower it in phases of predictable recession. Such a framework allows discussion of how growth trends may be disturbed over time as the result of changes in consumer sentiment.

Endogenous growth models are generally designed to address long‐term trends of growth. They explain how the economy converges with or diverges from a balanced growth path and they characterize aggregate behavior, given the optimization problem faced by a representative agent that maximizes consumption utility. In such frameworks, only potential output matters and all decisions, by firms and households, are taken on the assumption that any expectations on the value of the output gap do not interfere with the agents' behavior. Introducing consumer sentiment, a conventional growth model is modified in order to understand how effective output eventually deviates from the balanced growth path.

The proposed framework allows one to introduce nonlinear dynamics into the model, making it feasible to obtain, for reasonable parameter values, endogenous fluctuations. These are triggered by a Neimark‐Sacker bifurcation.

By introducing consumer confidence or consumer sentiment, it is possible to integrate the evaluation of growth and cycles into a unified framework. It is possible to explain business cycles as the result of the consumers' reaction to the expected performance of the economic system.

Recently, star variables and the post-crisis nature of cyclical fluctuations have attracted a great deal of interest. In this chapter, the authors investigate different methods of assessing business cycles (BCs) for the European Union in general and the euro area in particular. First, the authors conduct a Monte Carlo (MC) experiment using a broad spectrum of univariate trend-cycle decomposition methods. The simulation aims to examine the ability of the analysed methods to find the observed simulated cycle with structural properties similar to actual macroeconomic data. For the simulation, the authors used the structural model’s parameters calibrated to the euro area’s real gross domestic product (GDP) and unemployment rate. The simulation outcomes indicate the sufficient composition of the suite of models (SoM) consisting of popular Hodrick–Prescott, Christiano–Fitzgerald and structural trend-cycle-seasonal filters, then used for the real application. The authors find that: (i) there is a high level of model uncertainty in comparing the estimates; (ii) growth rate (acceleration) cycles have often the worst performances, but they could be useful as early-warning predictors of turning points in growth and BCs; and (iii) the best-performing MC approaches provide a reasonable combination as the SoM. When swings last less time and/or are smaller, it is easier to pick a good alternative method to the suite to capture the BC for real GDP. Second, the authors estimate the BCs for real GDP and unemployment data varying from 1995Q1 to 2020Q4 (GDP) or 2020Q3 (unemployment), ending up with 28 cycles per country. This analysis also confirms that the BCs of euro area members are quite synchronized with the aggregate euro area. Some major differences can be found, however, especially in the case of periphery and new member states, with the latter improving in terms of coherency after the global financial crisis. The German cycles are among the cyclical movements least synchronized with the aggregate euro area.

Transportation plays a central role in facilitating economic activities across sectors and between regions and thus should be essential to business cycle research. In this chapter, we identify four coincident indicators representing different aspects of the transportation sector. Foremost among them is the index of transportation services output (TSI) presented in the previous chapter. Following the long-standing methodology of National Bureau of Economic Research (NBER) business cycle research, the other three indicators that we include are payroll, personal consumption and employment – all pertaining to the transportation sector. Using a composite of the four indicators, we define the classical business cycle and growth cycle chronologies for the transportation sector. We find that, relative to the economy, business cycles in the transportation sector have an average lead of nearly 6 months at peaks and an average lag of 2 months at troughs. Similar to transportation business cycles, growth slowdowns in this sector also last longer than the economy-wide slowdowns by a few months. This study underscores the importance of transportation indicators in monitoring cyclical movements in the aggregate economy.

The paper aims first of all to identify the stage of the life cycle of rapidly growing Lithuanian enterprises and the main challenges that management faces at a particular stage.

The methodology of the study is based on the research works carried out by Hanks and Watson, Miller and Friesen and Kazanjian. On the basis of the selected factors an original questionnaire was developed and administered to eight Lithuanian companies.

Main findings of the empirical study show that rapidly growing Lithuanian companies correspond to the main life cycle features and face specific problems that were partially reported by numerous research works but also some unique ones. Findings confirm the reliability of the life cycle studies.

The research could be extended to the broader sample, especially into different sectors. Also it would be beneficial to carry out the study in different countries with developing economies to test unique findings of the research.

The findings can be used by managers to predict and prepare for meeting effectively the challenges associated with certain stages of enterprise growth.

The paper is a first attempt to apply organisational life cycle theory in order to systemise the challenges that Lithuanian enterprises face, and to contribute to the development of the debate on organisational life cycle theory reliability.

The purpose of this paper is to propose the new dependences of cycles to failure for a given initial crack length upon the stress amplitude in the linear fracture approach. The anticipated unified propagation function describes the infinitesimal crack-length growths per increasing number of load cycles, supposing that the load ratio remains constant over the load history. Two unification functions with different number of fitting parameters are proposed. On one hand, the closed-form analytical solutions facilitate the universal fitting of the constants of the fatigue law over all stages of fatigue. On the other hand, the closed-form solution eases the application of the fatigue law, because the solution of nonlinear differential equation turns out to be dispensable. The main advantage of the proposed functions is the possibility of having closed-form analytical solutions for the unified crack growth law. Moreover, the mean stress dependence is the immediate consequence of the proposed law. The corresponding formulas for crack length over the number of cycles are derived.

In this paper, the method of representation of crack propagation functions through appropriate elementary functions is employed. The choice of the elementary functions is motivated by the phenomenological data and covers a broad region of possible parameters. With the introduced crack propagation functions, differential equations describing the crack propagation are solved rigorously.

The resulting closed-form solutions allow the evaluation of crack propagation histories on one hand, and the effects of stress ratio on crack propagation on the other hand. The explicit formulas for crack length over the number of cycles are derived.

In this paper, linear fracture mechanics approach is assumed.

Shortening of evaluation time for fatigue crack growth. Simplification of the computer codes due to the elimination of solution of differential equation. Standardization of experiments for crack growth.

This paper introduces the closed-form analytical expression for crack length over number of cycles. The new function that expresses the damage growth per cycle is also introduced. This function allows closed-form analytical solution for crack length. The solution expresses the number of cycles to failure as the function of the initial size of the crack and eliminates the solution of the nonlinear ordinary differential equation of the first order. The different common expressions, which account for the influence of the stress ratio, are immediately applicable.

Since the transportation sector plays an important role in the initiation and propagation of business cycles, in previous chapters we developed output [transportation services output (TSI)] and other indicators to construct an index of coincident indicators for the U.S. transportation sector to identify its current state. We defined the reference cycle, including both business and growth cycles for this sector beginning in 1979 using both the conventional National Bureau of Economic Research (NBER) method and modern time series models. A one-to-one correspondence between cycles in the transportation sector and those in the aggregate economy was found; however, both business and growth cycles of transportation often start earlier and end later than those of the overall economy. Although the knowledge and inference based on coincident indicators can serve as an important reference for planning and other decision-making processes, these indicators are also subject to substantial lag due to data collection, processing and revision, underscoring the need to develop a system of leading indicators for the industry. Thus, in this chapter, we construct an index of leading indicators for the transportation sector as a forecasting tool using rigorous statistical procedures.

The authors analyse a growth model to explain how economic fluctuations are primarily driven by productive capacities (i.e. capacity utilization driven by innovations and know-how) and productive inefficiencies.

This study’s methodology consists of the combination of the economic growth model, à la Solow–Swan, with a sigmoidal production function (in capital), which may explain growth, poverty traps or fluctuations depending on the relative levels of inefficiencies, productive capacities or lack of know-how.

The authors show that economies may experience economic growth, poverty traps and/or fluctuations (i.e. cycles). Economic growth is reached when an economy experiences both a low level of inefficiencies and a high level of productive capacities while an economy falls into a poverty trap when there is a high level of inefficiencies in production. Instead, the economy gets in cycles when there is a large level of the lack of know-how and low levels of productive capacity.

The authors conclude that more capital per capita (greater savings and investment) and greater productive capacity (with less lack of know-how) are the economic policy keys for an economy being on the path of sustained economic growth.