Investment-specific Technology Shocks Research Articles

Investment-specific technology shocks and business cycle: evidence from a sign restriction approach

Investment-specific technology shocks and business cycle: evidence from a sign restriction approach

Estimation of industry-level basic digital capital services in China: A variable depreciation rate estimation method based on DSGE

Accurately measuring the input of digital capital is of great significance for understanding the development pattern of China's digital economy, nurturing new quality productivity, and achieving high-quality development. However, existing representative studies often assume a constant depreciation rate for capital goods, which does not align with reality. In this paper, we address this limitation by introducing dynamic stochastic general equilibrium (DSGE) model that estimates the variable depreciation rate for each capital good. By setting the depreciation rate as a function of capital maintenance expenditures and utilization rates, we provide a more realistic approach. The empirical results obtained through Monte Carlo simulation demonstrate that the trend of depreciation rates for all types of capital goods aligns with China's economic development. Additionally, we find that investment-specific technology shock plays a significant role in affecting changes in the depreciation rates of capital goods. This shock leads to an increase in capital utilization rates and a decrease in capital maintenance expenditures, resulting in higher depreciation rates. Notably, the depreciation rate of basic digital capital is more sensitive to exogenous shock compared to non-digital capital. Furthermore, the paper estimates the basic digital capital service of 19 industries in China from 1981 to 2020. The results indicate a steady increase in the services provided by basic digital capital, with particularly rapid growth observed in industries such as information transmission, software and information technology services, and the financial sector. When comparing our estimation results with those of representative literature, we find that the national-level productive capital stock and the basic digital capital services estimated using our methodology closely align with existing literature. This validation confirms the effectiveness of our methodology and the reliability of the estimated industry-level basic digital capital services.

Output measurement and technological shocks in business cycles

ABSTRACT Is the importance of technology shocks in accounting for the fluctuations in output and hours sensitive to the measure of output? Using a vector autoregression, we empirically investigate the contribution of technological shocks to economic fluctuations when output is defined in consumption units, as commonly used in many macroeconomic models, and when output is tabulated according to the Divisia index in the U.S. National Income and Product Accounts (NIPAs). Based on a standard neoclassical growth framework that allows for a mapping of theory into any desired measure of output, we establish that the same restrictions may be used to identify technology shocks in a vector autoregression model regardless of the measure of output. However, our estimation reveals that while the combination of both investment-specific technology shocks and neutral technology shocks accounts for a large portion of the business cycle variability of hours and output, the choice of the measure of output via the use of the associated deflator greatly affects the amplification of the shocks in the responses and the variability of the responses in output and hours.

Are all economic fluctuations bad for consumers?

Are business cycles always costly? This paper sheds new light on this question in the context of a two-sector neoclassical business cycle model by focusing on the roles of the origin of shocks and the degree of real frictions that restrict factor reallocation both inter-temporally (investment adjustment cost) and intra-temporally (inter-sectoral factor immobilities). We find that under the benchmark parameterization, investment-specific technology shocks are welfare-improving while consumption-specific technology shocks are welfare-detrimental, regardless of the degree of real frictions. While aggregate TFP shocks can be both depending on the degree of real frictions, welfare-improving business cycles are not supported by empirical evidence.

Business cycle dynamics when neutral and investment-specific technology shocks are imperfectly observable

We develop a general equilibrium business cycle model with imperfectly observed neutral and investment-specific technology shocks, which agents learn from noisy signals. Estimated using US data, the model implies that neutral technology shocks generate more volatile responses than in an environment with perfect information, whereas investment-specific shocks have more persistent impact. Noise accounts for substantial variation in investment, and alters agents’ behavior persistently through its influence on beliefs — even when the underlying fundamentals are unchanged and the noise itself is not persistent. Further implications for business cycle analysis are explored.

Are neutral and investment-specific technology shocks correlated?

The joint behavior of Total Factor Productivity (TFP) and the Relative Price of Investment (RPI) in the data lead several authors to conclude that neutral technology shocks are positively correlated with investment-specific technology shocks, challenging the specification of standard macroeconomic models. This paper rejects the correlated-shocks hypothesis using both parametric and non-parametric methods and controlling for structural breaks. The data suggests moderately negative long-run covariation between the RPI and TFP constructed from chain-linked output, but the RPI is orthogonal to TFP in consumption units. These results are consistent with a simple two-sector model in which neutral technology shocks and investment-specific technology shocks are uncorrelated, while models with correlated shocks cannot account for the second result. I conclude that it is not necessary to adapt macro models to allow for correlated technology processes.

Technology shocks and sectoral labour market spill-overs

In a multi-sector model estimated on U.S. data, we apply standard long-run restrictions to investigate the labour market consequences of investment-specific and neutral technology shocks. We set up a global VAR model where aggregate technology shocks feed onto sector-specific dynamics and then propagate back through the network structure of the economy. At the aggregate level, our results are consistent with the wealth of existing empirical studies where investment-specific technology shocks trigger favourable employment responses, in contrast to neutral technology shocks. At a disaggregate level, however, we uncover the significant contribution of sectoral spill-overs in response to technology shocks, particularly in driving the adjustment towards long-term equilibrium.

The Dynamic Effect of Micro-Structural Shocks on Private Investment Behavior

This paper estimates the dynamic effect of three micro-structural shocks, namely, investment-specific technology, markup and technology shocks to key components of the Iranian economy: private investment behaviour. The identification strategy positions the structural shocks to private investment behaviour in the Dynamics Stochastic General Equilibrium (DSGE) framework with a three-accuracy test estimation: The Brooks and Gelman test, the Metropolis-Hastings jumping distribution acceptance ratio, and the distribution of the deep posteriors parameters are asymptotically normal. The quarter economic data of Iran economy from July 1988 until March 2015 is applied. The findings illustrate that the structural shocks about technology have a similar impact and cause a growth in private investment, and the only difference is, in investment-specific technology shock due to a temporary decrease in the capital expenses installation (Tobin's Q), an investment boom is driven. In contrast, the price markup shock due to inflation causes a decline in all investment indices.

The Impact of Investment-Specific Technology Shocks on Macroeconomics Variables

The Impact of Investment-Specific Technology Shocks on Macroeconomics Variables

Observed expectations, news shocks, and the business cycle

This paper exploits information from the term structure of survey expectations to identify news shocks in a DSGE model with rational expectations.We estimate a structural business-cycle model with price and wage stickiness. We allow for both unanticipated and anticipated components (“news”) in each structural disturbance: neutral and investment-specific technology shocks, government spending shocks, risk premium, price and wage markup shocks, and monetary policy shocks.We show that the estimation of a standard DSGE model with realized data obfuscates the identification of news shocks and yields weakly or non-identified parameters pertaining to such shocks. The identification of news shocks greatly improves when we re-estimate the model using data on observed expectations regarding future output, consumption, investment, government spending, inflation, and interest rates - at horizons ranging from one-period to five-periods ahead.The news series thus obtained largely differ from their counterparts that are estimated using only data on realized variables. Moreover, the results suggest that the identified news shocks explain a sizable portion of aggregate fluctuations. News about investment-specific technology and risk premium shocks play the largest role, followed by news about labor supply (wage markup) and monetary policy.

Decomposition of the Business Cycle Shock and the Default Rate of SMEs in Korea

This paper, through a structural VAR identified by a long-run restriction which is imposed by a neoclassical growth model, decomposes the real price index of capital accumulation (= deflator for fixed capital accumulations/consumption expenditure deflator), labor productivity (= real GDP/total employee hours), and total employee hours into three business cycle shocks: (i) investment-specific technology shock, (ii) neutral technology shock, and (iii) non-technology shock, and explores which shock has played a significant role in contributing to decreases in the default rate of SMEs. Empirical results drawn from Korean data spanning from 2000:Q1 to 2016:Q2 indicate that when the two technology shocks arise by 1%p, the default rate decreases by 0.03%p to 0.05%p permanently. In contrast, the impact of the non-technology shock on the default rate is highly transitory : the default rate decreases by 0.02%p in response to the 1%p increment in non-technology shock but turns back to its initial level after about three quarters. These imply the technology shocks could account for the most of variations in the default rate of SMEs. Our empirical results, therefore, deliver the policy implication that SME financing should focus on innovative firms with aggressive funding.

Investment Shocks and Asset Prices: An Investment-Based Approach

We propose a new approach, based on investment data, to determine firms’ return exposure to investment-specific technology (IST) shocks. When applied to U.S. data, we find that, in contrast to the pattern estimated from empirical IST proxies, value firms have higher exposure to IST shocks than growth firms. When applied to simulated data from existing theoretical models, our approach reveals that existing empirical findings may result from measurement errors in the IST proxies. Importantly, our simulation analysis uncovers the key role played by investment data in determining the economic mechanism through which IST shocks affect cross-sectional asset prices.

Investment specific technology shocks and emerging market business cycle dynamics

This article explores the role played by investment-specific technology (IST) shocks in emerging market business cycle fluctuations. The analysis is motivated by two key empirical facts; the presence of IST change in the post-war US economy combined with the importance of US investment goods in the emerging market imports. The goal is to quantify the contribution of US IST change for the business cycles of an emerging country in the context of a two-country, two-sector international real business cycle framework with investment and consumption goods sectors. Specifically, I estimate the model using Mexican and US data and find that a permanent US-originating IST shock is important in explaining Mexican business cycle dynamics. Shocks to investment sector technology explain around 60% of the investment, 44% of the consumption and 52% of the output variability. I argue that both a shock that captures financial frictions and a permanent US-originating IST shock are necessary to account for the key business cycle features in the data.

A Tale of Two Returns: Stock and Investment Returns with Investment Specific Technology Shocks

A Tale of Two Returns: Stock and Investment Returns with Investment Specific Technology Shocks

Capital Intensity and Investment Shocks: Implications for Stock Returns

I show that a firm's capital intensity determines the asset pricing implications of investment-specific technology shocks. Capital-intensive stocks sorted by exposure to the investment shock generate a highly significant abnormal return of up to 5% annually. This pattern of abnormal stock returns is absent among labor-intensive firms, although the exposures to the investment shock are similar. This finding is a puzzle since similar exposures to the investment shock generate very different average (abnormal) stock returns for capital-intensive and labor-intensive firms. To explain this puzzle, I extend prior models of the investment-specific technology shocks by a novel dimension; firm's capital intensity. The model can rationalize these empirical findings.

Workplace Organization and Asset Pricing

Flexible workplace organization (WO) increases the efficiency of a firm’s future capital investment. Hence, investment in WO positively predicts future capital investment and exposure to future aggregate investment-specific technology (IST) shocks. As a result, firms that invest in WO become riskier and systematically experience higher equity returns. This paper documents a robust positive correlation between firms’ WO investments and future equity returns. Firms with higher industry-adjusted WO investments have average returns that are 3.7% higher than those of firms with lower WO investments. In addition, firms with high WO investments experience a high conditional IST beta in the future. I tie all my empirical findings together in a production-based equilibrium model with closed-form solutions.

설비자본재 기술진보가 근로유형별 임금 및 고용에 미치는 영향 (The Effect of Investment-Specific Technology Shocks on the Gap of Wage and Employment by Workers′ Skill or Tasks)

Korean Abstract: 일반적으로 임금과 고용의 변화는 경기변동, 노동시장 제도변화, 교육수준 향상 등 노동수요 및 공급에 영향을 미치는 여러 요인의 영향을 받는다. 이중 생산기술의 변화는 생산과정에서의 노동투입 결정에 변동을 가져와 임금과 고용에 영향을 미치게 되는데, 노동력이 다양한 유형으로 구성된 경우에는 이들 간 임금 및 고용 변화에 차이를 가져올 수 있다. 본 논문은 이러한 기술변화 중 설비자본재의 기술진보를 가져오는 양( )의 투자고유충격(investment- specific technology shocks; 이하 IST충격)이 근로자의 근로유형별 임금 및 고용의 격차(비율)에 어떤 영향을 미치는지 중점적으로 분석하였다. 학력별(대졸이상/고졸이하)로 근로유형을 구분(숙련/미숙련)하고, IST충격·숙련편향적 기술충격·숙련편향外 기술충격이 각각 발생할 때 이들 간의 임금격차(숙련프리미엄), 고용격차(상대고용)가 어떻게 변화하는지 알아보았다. 장기제약을 도입한 구조 베이지안 VAR모형으로 투자고유충격(IST충격) 등 각각의 기술충격을 식별하였다. 또한, 본 논문에서 처음 시도된 것으로써, 직업의 직무특성별(반복·정형업무/非정형업무)로도 근로유형을 구분(정형직/비정형직)하고, IST충격·정형직노동 생산성충격·그 외 기술충격이 이들 간 임금격차와 고용격차에 미치는 효과도 분석하였다. 분석결과, 설비자본재 기술진보를 의미하는 양( )의 IST충격은 숙련-미숙련 근로자 간 임금격차는 축소시키고 정형-비정형직 근로자 간 임금격차는 확대시켰다. 다만, 동 충격으로 숙련 및 정형직 근로자의 고용격차는 유의하게 변화하지 않아 고용구조 변화까지는 초래하지 않았다. 이러한 분석결과를 통해 우리나라의 설비자본은 생산과정에서 미숙련근로자에 비해 숙련근로자를, 정형직 근로자에 비해 비정형직 근로자를 더 많이 대체하는 특성을 보이고 있음을 알 수 있었다. English Abstract: This paper aims to assess the effect of investment-specific technology shocks(IST shocks) on the gap of wages and employment between different groups of workers in the Korean labor market. IST shocks can be identified by four long-run restrictions in a Structural Bayesian VAR framework. First, workers are categorized into skilled(college graduates and more) and unskilled(high-school graduates and less) ones by their educational attainment. After each shocks activates, including IST·skill-biased technology·other technology shocks, changes in the Skill-Unskill wage gap(skill premium) and employment differentials are examined. Second, workers are re-categorized into routine(tasked on repetitive and procedural jobs) and non-routine ones by their occupational tasks. By simulating IST·routine-labor productivity·other technology shocks respectively, it is originally checked how the Routine-Nonroutine wage gap and employment differentials will change. This paper shows that positive IST shocks can decrease the Skill-Unskill wage gap and increase the Routine-Nonroutine wage gap. It is also found, however, that positive IST shocks can not drive significant changes in employment differentials by any categorization.

Product Market Competition and the Profitability Premium

This paper studies the impact of product market competition on the well-documented positive relation between firms' current profitability and future stock returns. I find that this relation is robust only in competitive industries. A long-short portfolio sorted on profitability earns an average monthly return of 1.1% in competitive industries and only 0.14% in concentrated industries. Firms' differential exposure to investment-specific technology shocks explains this gap. To understand this result, I build a production-based model with imperfect competition. Market power reduces a firm's investment response to these shocks and thus lowers risk exposure. Empirical tests confirm the model's predictions.

Can Investment Shocks Explain the Cross Section of Equity Returns?

Using two macro-based measures and one return-based measure of investment-specific technology (IST) shocks, we find that over the 1964–2012 period, exposure to IST shocks cannot explain cross-sectional return spreads based on book-to-market, momentum, asset growth, net share issues, accrual, and price-to-earnings ratio. Only one of the two macro-based measures can explain a sizable portion of the value premium over the longer 1930–2012 period. We also find that the IST risk premium estimates are sensitive to the sample period, the data frequency, the test assets, and the econometric model specification. Impulse responses of aggregate investment and consumption indicate potential measurement problems in IST proxies, which may contribute to the sensitivity of IST risk premium estimates and the failure of IST shocks to explain cross-sectional returns. This paper was accepted by Neng Wang, finance.

Do business cycles, investment-specific technology shocks matter for stock returns?

This paper empirically analyzes the dynamic relationship between business cycle, investment-specific technology shocks, and stock returns in the Indian context. Using Structural VAR technique the study finds: (1) business cycle shocks and stock market returns are more pronounced, especially during the financial market liberalization (2) the dominant role of global cycles over country cycles in explaining stock returns (3) interest rate plays an important role to interact the business cycle dynamics and stock returns (4) a relatively weak effect of investment-specific technology shocks on the business cycle and stock returns.