Set Of Control Variables Research Articles

The evolution of energy efficiency impact on housing prices. An analysis for Metropolitan Barcelona

The Energy Performance of Buildings Directive has it made mandatory to include an energy performance certificate (EPC) on real estate advertisements so as to promote efficient properties. Previous research has found a positive correlation between residential prices and EPC’s energy ranks; nonetheless, the analysis of the evolution of such impact for the same market is still pending. This paper tries to shed light on this issue by analyzing the evolution of prices of the second largest urban agglomeration in Spain. In doing so, a pooled hedonic model is carried out departing from selling listing prices of apartments and a set of locative control variables. Results suggest that in a short period the energy premium for multifamily houses has positively evolved. As a result, a sharped market differentiation arises between inefficient and energy saving dwellings. Such findings have significant implications for the construction and real estate industry, since higher selling prices may compensate for higher building costs coming from energy efficient technologies.

Lasting effects of promoting literacy – do when and how to learn matter?

ABSTRACTThis paper analyzes the lasting impacts of a project aimed at teaching children how to read and write at age 6. Using a Difference-in-Differences methodology, the results show that it is not enough to get children literate at age 6 to secure lasting effects; the instruction process is also an important factor: Only pupils exposed to the Phonics method were able to perform better than controls in a Language exam four years later. The results are robust for a large set of time-varying control variables, including the socioeconomic status of the children, the main variable associated with school performance.

The Looming Central and Eastern European Real Convergence Club. Do Implicit Tax Rates Play a Part?

Abstract The paper investigates whether there is a convergence club stance for the Visegrad countries plus Romania and Bulgaria and the part played, in this process, by the implicit tax rates on labour and consumption, respectively. For the purpose of the research, the GDP per capita, productivity and unemployment are used as convergence indicators and dependent variables. The dataset covers the 1995–2016 timeframe and the analysis is based on a panel-model approach. The main results show that the implicit tax on labour has no significant effect on the convergence indicators while the implicit rates on consumption are statistically significant with negative influence. The interpretation of results is made considering a set of control and robustness variables where policy lessons derive from. The conclusion reflects on the policy lessons that can serve to accomplish the convergence club within selected CEE countries: Bulgaria, the Czech Republic, Hungary, Poland, Slovakia and Romania.

Interpretable machine learning for inferring the phase boundaries in a nonequilibrium system.

Still under debate is the question of whether machine learning is capable of going beyond black-box modeling for complex physical systems. We investigate the generalizing and interpretability properties of learning algorithms. To this end, we use supervised and unsupervised learning to infer the phase boundaries of the active Ising model, starting from an ensemble of configurations of the system. We illustrate that unsupervised learning techniques are powerful at identifying the phase boundaries in the control parameter space, even in situations of phase coexistence. It is demonstrated that supervised learning with neural networks is capable of learning the characteristics of the phase diagram, such that the knowledge obtained at a limited set of control variables can be used to determine the phase boundaries across the phase diagram. In this way, we show that properly designed supervised learning provides predictive power to regions in the phase diagram that are not included in the training phase of the algorithm. We stress the importance of introducing interpretability methods in order to perform a physically relevant classification of the phases with deep learning.

Day care quality and changes in the home learning environment of children

ABSTRACTChildren's development is fostered by both high quality Early Childhood Education and Care (ECEC) settings and high quality home learning environments. As we know little about the interrelations between these two environments, we examine whether the child's attendance in a high quality ECEC arrangement relates to the quality of her home learning environment. Using rich NICHD Study of Early Child Care and Youth Development data, we show that ECEC quality is associated with the home learning environment, even after taking into account the lagged dependent variable and a rich set of control variables.

Exploring the contribution of unconventional parameters on spark gap formation and its minimization during WEDM of layered composite

Cladded materials are heterogenous in nature and considered as difficult-to-cut especially via conventional machining operations. Gas and/or plasma cutting are common in practice to cut clad materials. However, these processes induce deeper heat-affected zones and provide very rough surface integrity. Wire electric discharge machining (WEDM) is a capable alternate yielding better cut quality. Formation of a significant spark gap between the cut surfaces is the iconic problem of WEDM which is addressed in this study. WEDM has been performed on stainless-clad steel with a focus on identifying the significant parameters affecting the amount of spark gap and its minimization in the final cut. Eight input control factors, namely workpiece orientation, thickness of individual layer, servo voltage, pulse on-time, wire diameter, wire feed, and pressure ratio, have been employed to investigate their effects on spark gap development. Experimentation has been performed according to L18 orthogonal array followed by comprehensive statistical analyses. ANOVA shows that wire diameter and pressure ratio are the two main influential parameters for spark gap having percentage contribution of 71% and 16%, respectively. Optimal settings of control variables are also achieved through S/N ratio analysis. Improvement of 23.4% towards spark gap reduction is realized.

Explaining success of performance management systems

PurposeThe purpose of this paper is to use the logical chain of key factors (KFs) to explain the success of performance management systems (PMS) and corporate performance.Design/methodology/approachThe authors use the strength of the KFs chain to capture PMS success. First, the authors assume that perceived environmental uncertainty (PEU) is positively associated with the strength (H1). The higher the PEU, the stronger is the chain as a response to uncertainty. Second, the authors assume that the strength improves performance (H2) but third, that the impact of the strength is negatively moderated by competition (H3). Fourth, the authors assume that this improvement leads to superior corporate performance (H4). The research model is tested by applying the partial least squares method for a sample of 61 Estonian and Finnish firms.FindingsEmpirical evidence shows that PEU is negatively correlated to the strength of the chain but when controlled for a set of control variables, the path coefficient is positive. The strength of the chain is positively associated with improvement in performance. The impact of the strength of the chain on financial performance is negatively moderated by competition. The improvement in performance is positively associated with the attainment level of strategic goals. The improvement in non-financial performance does not significantly affect corporate profitability.Practical implicationsThe levels of PEU and competition should be taken into the account when designing, adjusting and assessing the PMS of organization.Originality/valueThe authors give explanation why evidence about the effects of PMS on the performance of the firm is mixed.

Multiobjective Operation Optimization of Continuous Annealing Based on Data Analytics

Continuous annealing production process generally consists of multiple complex processes that are coupled to each other, and each process contains many control variables. It is difficult to establish a precise mechanism model of the production process. The operators mainly set these control variables based on past production experience, which often result in great fluctuations of product quality (even unqualified products) and high energy consumption. This in turn significantly affected production cost and economic benefits of the cold rolling mill. To efficiently handle this problem, an ensemble learning modeling method based on production data is first proposed for this production process, and then, a multiobjective operation optimization model is established to optimize the operation of continuous annealing production process. Finally, an improved multiobjective differential evolution algorithm based on search process memory is developed to solve this model and achieve the optimal setting of control variables. The computational results on both benchmark problems and practical problems illustrate that the proposed algorithm is superior to some powerful multiobjective evolutionary algorithms in the literature and it can effectively achieve good setting of control variables for the continuous annealing production process.

Short Selling and Firm Investment Efficiency

This paper investigates the informativeness of short sales on detecting a firm’s investment inefficiency. We document that short sellers adjust their short positions before the financial statement announcements to utilize their information advantage on firms’ investment inefficiency. The relationship between a firm’s short sale position and its future investment inefficiency is both statistically and economically significant, and robust to a broad set of control variables. Subsample analysis shows that the informativeness of short sales positions on future investment inefficiency concentrates on firms with low board independence and firms with low CEO incentive pay.

Immigration as a Social Determinant of Oral Health: Does the 'Healthy Immigrant Effect' Extend to Self-rated Oral Health in Ontario, Canada?

Immigrants' oral health is rarely explored in Canada, despite its impact on physical, social, and economic well-being. Drawing on data from the 2014 Canadian Community Health Survey, we address this void by comparing self-rated oral health among recent immigrants, established immigrants, and the native-born in Ontario, Canada. The analysis includes three sets of control variables capturing the resettlement stress perspective, convergence perspective, and selective immigration. We find that oral health does not significantly differ between recent immigrants and the native-born at the bivariate level, although the odds of reporting poor oral health become significantly lower for recent immigrants, once the resettlement characteristics are accounted for. This difference is completely attenuated by selective immigration characteristics. Established immigrants are more likely to report poor oral health than the native-born, even after accounting for all control variables. Based on these findings, we conclude by offering recommendations for policymakers.

‘No country for old men’? The multiplier effects of pensions in Portuguese municipalities

AbstractOne of the major findings of this paper, which studied the multiplier effects of pensions received at each Portuguese municipality since 2003, is that pensions stimulate the incomes of municipalities. We studied these effects also considering the spillovers from/to the surrounding areas. After discussing several models of spatial analysis, we chose the Dynamic Spatial Durbin Model. Our results were obtained after considering a proper set of control variables.

MoSiCS: Modeling, simulation and optimization of complex systems–A case study on energy efficient datacenters

This paper proposes a methodology for modeling and simulation the operation of Complex Systems considering the energy perspective which may feature both discrete and continuous as well as linear and nonlinear sub-systems. The methodology integrates in a unified view, sub-systems with behavioral or phenomenological models, each of them featuring a set of inputs, outputs and control variables with their associated actions. A proactive optimization process is defined in terms of system level flexibility as well as operation self-adaption, and is leveraging on model simulations to calculate over a time window the system outputs for a set of given inputs and actions. We aim to determine the optimal plan of actions over a set of predicted inputs that will minimize the distance between the system outputs and a given target. To prove its effectiveness, we model and simulate the thermal-electrical processes inside a Data Center, aiming to optimize its operation by exploiting the thermal energy flexibility to re-use the otherwise wasted heat in nearby neighborhoods.

Structural adjustment, state capacity and child health: evidence from IMF programmes.

Consensus is growing that policy reform programmes by the International Monetary Fund (IMF)-an international organization mandated with upholding global financial stability and assisting countries in economic turmoil-produce adverse effects on public health. However, this consensus is unclear about which policies of these programmes underlie these effects. This article fills parts of this gap by examining the impact of four kinds of IMF policies (fiscal policy, public-sector employment, privatization of state-owned enterprises and price liberalization) on public-health expenditure, child vaccination and child mortality. We conducted time-series cross-section analyses for up to 128 developing countries over the 1980-2014 period using observational data on health outcomes and IMF conditionality for different policy areas. IMF effectiveness research faces two types of potential biases: self-selection into IMF programmes and IMF policy conditions. We deployed instrumental variables in a seemingly unrelated regression framework to address both types of endogeneity, besides traditional remedies such as the use of fixed effects on countries and years. IMF policy conditions on public-sector employment are negatively related to child health. A change from the minimum to the maximum number of such policy conditions decreases vaccination (which ranges from 0 to 100) by 10.97% [95% confidence interval (CI): 1.16 to 20.79]. This effect is robust against different sets of control variables. In addition, IMF programmes increase the share of government expenditure devoted to public health in developing countries by 0.91 percentage points (95% CI: 0.15to 1.68). These findings suggest that IMF policies-particularly those that require public-sector reforms-undermine health by weakening the capacity of states to deliver vaccination. Therefore, international financial institutions need to increase their awareness of the public-health impact of their policy prescriptions. Strengthening state capacity in times of economic crisis would ensure that increased health spending also delivers quality healthcare.

What drives dividend smoothing? A meta regression analysis of the Lintner model

We revisit the view of dividend smoothing as one of the most robust findings in the empirical corporate finance literature by employing meta-regression analysis (MRA). Using 99 empirical studies that employ Lintner's dividend payout model we investigate the heterogeneity in reported dividend smoothing effects. We find evidence for (i) a mediocre degree of dividend smoothing across the analyzed literature, (ii) bi-directional publication bias -i.e. a tendency to preferably report positive and statistically significant smoothing as well as dividend smoothing coefficients close to zero (i.e. high speed of adjustment coefficients), and (iii) several drivers for the heterogeneity in reported smoothing coefficients such as the set of control variables or estimation technique. Our MRA can provide guidance for investors' expectations and future research on dividend smoothing.

Who Goes into STEM Disciplines? Evidence from the Youth in Transition Survey

This article presents an empirical analysis of access to post-secondary education (PSE) as it pertains to students in science, technology, engineering, and mathematics (STEM) programs, who are vital to the nation’s economic performance, especially with respect to its information and communication technology (ICT) sector. The analysis is based on the rich Youth in Transition Survey, Cohort A (YITS–A), which follows a representative sample of Canadian youth age 15 in 1999 through to the normal point at which PSE decisions are made. The main findings include that female students go into STEM disciplines at a much lower rate than male students, even after controlling for a broad set of control variables, including high school grades in math and science. Conversely, visible minorities, especially those who are first-generation immigrants, and particularly those from a specific set of regions, participate at much higher rates than others. These results have implications for the ICT talent pool of the future.

Public investment and food security: Evidence from the Hundred Billion Plan in China

This paper examines the causal effect of public investment on food output by exploiting a panel dataset covering a large central government program (Hundred Billion Plan) in China from 2007 to 2013. Based on an event study methodology, we find that public investment significantly increases food output by 4.34%. We find that the sources of the policy effect come mainly through improving productivity, which is driven by increases in fertilizer inputs by households and by the crowding in local government agricultural investments. Further, an ad-hoc benefit-cost analysis shows that the internal return rate (IRR) is 0.23% over a 20-year period. Our results are robust in terms of the assumption of parallel trends, the confounding effect from an alternative policy, the nonrandom selection issue of policy implementation, the inclusion of alternative sets of control variables, the treatment of outliers and the omitted variable biases.

Allocation of internally generated corporate cash flow in Africa

PurposeThe purpose of this paper is to examine how managers of African firms, operating in environments characterised by less developed capital markets and weak institutional structures, make use of their internally generated cash flows.Design/methodology/approachThe authors use a panel data methodology which regresses a particular use of cash flow (e.g. capital expenditure) on the internally generated operating cash flow of a firm and a set of control variables. The estimation of the regression model is done by ordinary least squares regressions. For robustness, the authors also estimate the models using system generalised method of moments to control for endogeneity and measurement error problems.FindingsThe authors find that managers of African firms hold most of their internally generated cash flows, and when they decide to spend, they allocate a higher proportion towards dividend payments; followed by debt adjustments; then to investments; and lastly, to equity repurchases.Research limitations/implicationsThe findings are consistent with the existence of a significant financial constraint in African markets, and the use of dividends to signal credit quality in relatively underdeveloped capital markets.Originality/valueThe authors provide a more extensive analysis of how a firm spends a unit of the incremental cash flow it generates. In particular, the analysis shows that beyond investments in capital expenditure, other cash flow uses (i.e. cash holdings, dividend payments, and adjustments in debt and equity capital) which have been largely overlooked in the literature are important to understanding the effects of financial constraints on corporate decisions. Also, the early empirical evidence on the cash flow allocations of African firms could be a step in the right direction in informing theory development in this area.

The determinants of entrepreneurship gender gaps: A cross‐country analysis

AbstractThis paper uses aggregate data from the International Labor Organization and microeconomic data from the European Values Study to quantify gender gaps in entrepreneurship, distinguishing between gender gaps in employership and in self‐employment, and study their main empirical determinants. Our sample consists of 40 European countries and varies broadly in terms of institutional background since it includes several ex‐Communist countries. In the aggregate data we observe a gender gap in employers of 59% and a gender gap in self‐employment of 36%. These gaps have remained roughly constant in the 2000–2017 period, although there are wide differences in both their levels and evolution over time and across countries. Using microeconomic data, we find that the incidence of entrepreneurship, employership, and self‐employment among men is much larger than among women, consistent with the gaps estimated using aggregate data. Our regressions show that these gaps are still sizable even after controlling for a large set of control variables that include marital status, age, education, number of children, wealth, the participation of parents and spouse in entrepreneurship, values toward women, social capital, and prior unemployment. We identify important differences between the determinants of these gaps in ex‐Communist countries and in high‐income ones.

Intellectual property rights, imitation, and development. The effect on cross-border mergers and acquisitions

ABSTRACTIn this paper, we analyze whether the recent global process of strengthening and harmonization of intellectual property rights (IPRs) affects decisions of cross-border mergers and acquisitions (M&As). We investigate if IPRs have a differential effect across sectors of different technology content and for countries of different development level. Also, we study how imitation abilities of target countries interact with the tightening of IPRs. Using data for the post-TRIPS period (1995–2010), we estimate an extended gravity model to study the bilateral number of M&As, including a measure of the strength of IPRs systems on target countries and a set of control variables usually considered as determinants of M&As. The estimation results verify the gravity structure for M&As and show that IPRs –and enforcement– influence decisions of cross-border M&As in all sectors regardless of their technological content. However, IPRs are more important in countries with high imitation abilities and in sectors of high-technology content. Furthermore, a strengthening of IPRs leads to a larger increase of M&As in developing countries than in developed countries. These results call the attention on the possible implications for least developed economies and challenge the adequacy of a globally harmonized IPRs systems.

Immigration, Ethnic Diversity, and Political Outcomes: Evidence from Denmark

AbstractI study the impact of immigration and increasing ethnic diversity on political outcomes in immigrant‐receiving countries, focusing on immigration and election outcomes in Danish municipalities between 1981 and 2001. A novel instrumental variable strategy based on historical housing stock data addresses issues of endogenous location choices of immigrants and a rich set of control variables is employed to isolate ethnic diversity effects from those of other immigrant characteristics. Increases in local ethnic diversity lead to rightward shifts in election outcomes by shifting electoral support away from traditional “big government” left‐wing parties and towards anti‐immigrant nationalist parties. This holds for both local and national elections.