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Output growth uncertainty is a key issue in climate economics, involving the full range of impacts from emissions, through temperature changes to economic damage. The current study introduces output growth uncertainty into the EZ climate model, in which the predicted global carbon emissions under output growth uncertainty are used as weighted input. The objective of the present study is to calculate the future carbon prices represented by marginal abatement cost (MAC), to maximize social welfare. Moreover, the sensitivity of the two output growth uncertainty parameters, namely population growth rate and per capita output growth rate, is analyzed. Lastly, the significance and influence of output uncertainty for carbon price are also discussed. The results exhibit that (1) the optimal prices of per ton CO 2 e emission permits in the years 2020, 2030, 2060, 2080, and 2095 are $294.9, $285.3, $238.0, $143.3, and $15.4, respectively. (2) Population growth rate and per capita output growth rate both positively increase the future carbon prices, while the per capita output growth rate has a greater effect. (3) Compared with the performance under output certainty, carbon prices are estimated to be lower with output uncertainty; the high degree of uncertainty about carbon price is also primarily due to the high degree of output uncertainty. These results highlight the importance of research on output growth uncertainty, thus underpinning the EZ climate model for reducing carbon price and improving policymaking.

By means of stochastic volatility in the mean model to allow for time-varying parameters in the conditional mean and quarterly data for the G7 countries, this article examines the dynamic nexus between the volatility of output and economic growth for the G7 countries. This approach allows us to model parameter time-variation so as to reflect changes in the effect of volatility appearing in both the conditional mean and the conditional variance. The evidence in this article indicates that the effect of output volatility on output growth is strongly time-varying and quite analogues for all the G7 countries, with a break around 1973. The effect of output volatility on growth becomes more negative after 1973, with negative and statistically significant estimates after 1973 or early 1990s. Our estimates show a reversal of the declining trend and a significant increase in output volatility in the late-2000s, indicating that the Subprime Crisis brought a temporary break in the Great Moderation. However, the Great Moderation seems to be generally restored by the mid-2010s. The effect of output growth on output volatility is insignificant for all countries except for Italy and the US, for which the estimates are positive and statistically significant. Our estimates also show that output volatility is counter-cyclical for all countries.

Survey respondents who make point predictions and histogram forecasts of macro-variables reveal both how uncertain they believe the future to be, ex ante, as well as their ex post performance. Macroeconomic forecasters tend to be overconfident at horizons of a year or more, but overestimate (i.e., are underconfident regarding) the uncertainty surrounding their predictions at short horizons. Ex ante uncertainty remains at a high level compared to the ex post measure as the forecast horizon shortens. There is little evidence of a link between individuals' ex post forecast accuracy and their ex ante subjective assessments.

Since the 1990s, central banks in many industrialized and developing countries have adopted similar policy strategies for stabilizing inflation. In this context, it has been argued that during common policy periods, the relationships between inflation, output growth, and their uncertainties are stable and more uniform across countries. We intend to verify this for 19 countries using both linear and non-linear bivariate GARCH-in-mean models. According to our findings, the non-linear regime-dependent model performs better in most of the sampled countries. It has been observed that inflation uncertainty has a significant impact on inflation, particularly in developing countries. Nominal and real uncertainty affect output growth primarily during periods of economic contraction. Although nominal uncertainty inhibits output growth, real uncertainty has mixed effects. In most countries, negative growth shocks result in greater output growth volatility than positive growth shocks. Furthermore, in some countries, output growth significantly increases inflation only in high-inflation regimes.

Household debt levels relative to GDP have risen rapidly in many countries over the past decade. We investigate the relationship between household debt and growth by employing a novel estimation technique which helps to separate short-run from long-run relationships. Using data for 54 economies over 1990‒2016, we show that an increase in household debt is associated with higher GDP growth in the short run, mostly within one year. By contrast, a 1 percentage point increase in the household debt-to-GDP ratio predicts lower GDP growth in the long run by 0.1 percentage point. Moreover, the negative long-run relationship between household indebtedness and GDP growth intensifies as the household debt-to-GDP ratio exceeds 70%, suggesting that policy makers are likely to face non-trivial, real costs in stimulating the economy through credit expansion.

Purpose Human capital flight from developing countries to developed nations has been rising and giving concerns to governments and scholars alike. This paper aims to explore the impact migration from Nigeria has on economic output growth by focusing on the migration rate, remittances, population growth and secondary school enrolment. This has not received adequate attention in the literature, as many papers have primarily focused on the impact of remittances on economic growth. Design/methodology/approach Leveraging on the macro-level approach to migration, remittances and the economy, this research considers the nexus among the human capital flight and output growth variables by using the autoregressive distributed lag (ARDL) method of analysis for time series data between 1986 and 2018. Findings The net migration rate from Nigeria was found from the empirical analysis to be more disadvantageous for the economy, given its negative relationship with economic growth despite the large volume of foreign incomes (remittances). It also shows that secondary school enrolment positively and significantly impacted the Nigerian growth rate in the long run. Originality/value This research has widened the use of variables by combining net migration rate, remittances from abroad, population growth rate and secondary school enrolment to obtain a more robust outcome with implications for research and practice.

Building upon recent developments in production function identification and decomposition methods, this paper investigates the sources of output and productivity growth among China’s listed manufacturing companies from 2000 to 2022. While previous studies on China’s manufacturing have predominantly focused on the period preceding 2007, our study extends the analysis to a broader timeframe and divide it into four sub-periods to accommodate diverse economic conditions and varying growth rates. We provide new insights into the Chinese economy during a period marked by gradual economic transformation. Specifically, we first decompose industry output growth into factor deepening and firm productivity progress within each sub-period. To account for heterogeneity across firms in terms of production technology and sources of growth, we employ a nonparametric production function and decompose firm output growth at both the mean and different quantiles of the output distribution. We find that increased materials usage and productivity growth are primary growth drivers. However, the contribution of productivity experiences a significant decline, particularly in recent years and among median-sized and large firms. Furthermore, we examine China’s industry aggregate productivity growth and its origins among state-invested, foreign-invested, and domestic private firms. Our findings suggest that reforms among state firms are the largest contributor to industry productivity growth before the 2008 financial crisis, whereas productivity progress of domestic private firms emerges as the sole significant driver in recent years. Additionally, there is no evidence of improvements in output reallocation efficiency within China’s manufacturing sector throughout our sample period.

We derive asymptotic properties of estimators and test statistics to determine—in a grouped data setting—common versus group-specific factors. Despite the fact that our test statistic for the number of common factors, under the null, involves a parameter at the boundary (related to unit canonical correlations), we derive a parameterfree asymptotic Gaussian distribution. We show how the group factor setting applies to mixed-frequency data. As an empirical illustration, we address the question whether Industrial Production (IP) is still the dominant factor driving the U.S. economy using a mixed-frequency data panel of IP and non-IP sectors. We find that a single common factor explains 89% of IP output growth and 61% of total GDP growth despite the diminishing role of manufacturing.

We empirically test on a panel of OECD countries the hypothesis of a direct and positive link between funding of pensions and economic growth, which is based on the idea that richer pension systems can accelerate the development of the financial system and thus promote a more efficient capital allocation. We follow Davis and Hu (2008) in estimating a modified Cobb-Douglas production function where pension fund assets are treated as a shift factor, but in line with the recent econometric literature we control for common global shocks driving per capita outputs. Therefore we adopt a more general approach suitable to the presence of a multifactor error structure. The previous evidence of a long run cointegration relationship between autonomous (or total) pension fund assets and per capita output for our panel of OECD countries is not robust to our augmented specification.

This is a panel analysis for 28 African countries that focusses on investigating the mediating effect of economic complexity via resource-growth model in Africa between 1995 and 2019. We utilise the pool mean group (PMG) framework to analyse the panel series. Empirical result reveals that natural resources positively but insignificantly impact short- and long-run growth. For economic complexity, it exerts a significantly negative effect on growth in the short term but has a long-term favourable effect that is significant on growth. More so, the conditional impact of economic complexity and resource rent on economic growth is positive in both short- and long-run but only significant in the long run. Lastly, the study employs the economic complexity index plus to confirm the robustness of the empirical results. We therefore conclude that economic complexity is an important channel for promoting long-term resource blessing in Africa. The study then makes policies to improve the resource-growth link via the economic complexity channel.