+Corruption in a Process Duration [Invisible from Raw & Unrefined to Finished]

The production process was really interesting and had a lot of complexity to it.

Scheduling is the process of arranging, controlling and optimizing work and workloads in a production process. Companies use backward and forward scheduling to allocate plant and machinery resources, plan human resources, plan production processes and purchase materials.

Production scheduling tools greatly outperform older manual scheduling methods. These provide the production scheduler with powerful graphical interfaces which can be used to visually optimize real-time work loads in various stages of production.

We investigate the determinants of the efficiency of firms with a focus on the role of corruption. We construct a simple theoretical model where corruption increases factor requirements of firms because it diverts managerial effort away from factor coordination. We then exploit a unique dataset comprising firm-level information on 80 electricity distribution firms from 13 Latin American countries for the years 1994 to 2001. 

As predicted by the model, we find that more corruption in the country is strongly associated with more inefficient firms, in the sense that they employ more inputs to produce a given level of output. The economic magnitude of the effects is large. The results hold both in models with country and firm fixed effects. The results survive several robustness checks, including different measures of output and efficiency, and instrumenting for corruption. 

Other elements associated with inefficiency are public ownership, inflation, and lack of law and order, but corruption appears to play a separate and more robust role. 

We investigate the connection between corruption and the efficiency of electricity distribution firms in Latin America. We take advantage of a unique dataset comprising a panel of 80 electricity distribution firms from 13 Latin American countries for the years 1994 to 2001. Our data on corruption were provided by International Country Risk Guide and Transparency International.

Thus, corruption diverts managerial effort away from the productive process, and the way for firms to meet their service obligations is to use more inputs.3 Thus, the model predicts that more corrupt countries will have less efficient firms. The model is agnostic regarding the impact of corruption on profits, and it is compatible with stories of regulatory extortion against firms, regulatory capture, and internal corruption in firms. We then take the model to the data, and find that more corruption in a country is strongly associated with inefficiency, in the sense that firms employ more inputs to produce a given level of output.

Our main focus is on labor efficiency, so our default empirical strategy is to estimate a parametric labor requirement function to analyze the various determinants of labor use. Our result that corruption raises labor requirements holds under a variety of controls beyond basic firm features such as the size of output and capital inputs. Such controls include firm ownership type and the level of development in the country (as approximated by GNP per capita).

The characteristics of the industry and the countries in our sample favor comparability. Electricity distribution involves a mature technology that does not differ significantly across countries. Moreover, all the firms in our sample are from Latin American countries having the same colonial origins, relatively similar regulatory regimes, the same legal origins, and quite homogeneous cultural features. Nevertheless, our econometric specification includes controls varying by country and time such as the prevalence of law and order and indicators of macroeconomic instability. These controls help to disentangle the effects that corruption may have from those of other forces that may also affect efficiency. 

Corruption remains significant after including all of these controls. Inflation, inflation variation, and deficiencies in law and order appear themselves to be associated with greater inefficiency, especially in the firm fixed effects specification. This is interesting because it suggests that corruption plays a separate role that is distinct from the impact of a highly unstable or insecure environment. Of all the factors varying by country and time that we analyze, corruption is the only one that is both invariably significant across specifications and economically important. To check our focus on labor efficiency, we also estimate a model where we measure efficiency in terms of operation and maintenance expenditures, rather than in terms of labor. The significant negative association between corruption and efficiency persists. We also address several potentially serious problems for our estimation, such as the possibility of survey selection bias or results being driven by heterogeneity in degrees of vertical integration. We find no evidence that any of these elements drives results. A crucial aspect in the measurement of efficiency in energy distribution is the measurement of output. Our default measure of output is energy sales (in gigawatts hour—GWh). If energy theft is higher in more corrupt countries, the use of energy sales to measure output would make firms in more corrupt countries appear less efficient than they are. We provide a different treatment using sales plus losses as the output variable (which includes stolen energy) and find again that corruption is significantly associated with inefficiency.

In the case of private firms, they are regulated by an agency that is typically specific to the industry (electricity) or the sector (energy). In the case of publicly owned firms, they are under the oversight of a ministry-type governmental agency. The firms in our sample have the obligation to provide the service of electricity distribution to a given number of customers in a given geographical area. For modeling purposes, we will assume that firms are requested to produce an output of fixed size Q , which here is assumed to be a positive real number. The provision of this service requires the use of labor, capital, and managerial effort in the form of coordination and supervision of the use of labor and capital. Managers are able to improve the technology of the firm by exerting effort, in the sense that they can increase the rate at which capital and labor are transformed into output. Capital inputs are tightly dependent upon the extent of service, and treated in the literature on electricity distribution as exogenous in the short run (see Neuberg, 1977; and Kumbakhar and Hjalmarsson, 1998). For example, the firm’s transformation capacity and the extension of its network are tightly related to the number and type of customers to be served and the area over which they are scattered. Thus, variations in efficiency are largely connected with the use of labor. Unless stated otherwise, we say a firm is inefficient when it is not minimizing labor use given its output and capital stock. Given the exogeneity of capital, to save on notation we will consider the following production function,

Q = A(es)f(l)

where es—the managerial effort devoted to supervision and coordination—has the effect of raising total productivity A(.). The amount of labor used is denoted by l. We assume   s Aes > 0, Aeses < 0,  fl > 0, , , and fll < 0 (subscripts next to functions indicate arguments of differentiation throughout). The rationale for this formulation is that, given the number of workers, managers that tightly coordinate and supervise workers will elicit better performance and more output. Another view is that more workers might be required to make up for less attentive supervision. For example, a manager that devotes all his time to overseeing employees can receive information on the state of different transformers and connections from many inspectors scattered on the field. He can then direct a single repair team to each location that comes to need attention. A manager that is not available to receive information and give orders may have to rely on associating repairmen to each one of the inspectors, so that they can execute repairs if needed (thus raising the number of employed repairmen). With variations, this basic story can be told to capture what happens at different levels of the hierarchy in an electric utility. 

It is important to note that, given the contractual obligation to provide Q units of output, the use of l units of labor will imply that managers must provide exactly 

units of supervision effort. This is an important part of our model: a feature specific to the industry analyzed (an exogenous service obligation) determines the relationship between supervision and labor use. Another important part of the model is managerial payoffs. We assume that managers care about their total material rewards y and about the total effort e they exert:

 y−ψ (e),

where the cost of effort ψ (.) is increasing and convex. As will be explained shortly, the total effort e is the sum of effort deployed in various activities. The total rewards y to those running the firm stem from various sources. Managers are typically not the owners of the firm, but they can be expected to care about profits if higher profits trigger higher compensation and perks. Often managers may also pursue objectives that do not generate profit, like rendering services to a political party. In the discussion at the end of the section, we explain how such objectives can be incorporated in the model. For expositional reasons, here we adopt the simplest model possible that captures the effect of interest. So for now, we assume that managers have a stake in profits. Even in public firms where managerial incentives may be less high-powered—and conditional on the pursuit of other objectives—higher profits are likely to benefit managers, if only because higher profits allow more latitude in pursuing other goals. Given this, and to maximize simplicity, we will now abstract from the difference between managers and owners, and suppose that managers care directly about profits (in the discussion at the end of the section we explain how to reintroduce the distinction between owners and managers in the model). Thus, we will write y = π . Profits, in turn, are given by, 

where w are wages paid to workers, and p(.) is the price of a unit of service. This formulation captures the fact that the price charged by the firm may depend on its efforts ep at negotiating with the government and on the degree of corruption in the country. In non-corrupt countries prices are seen as being close to what industry jargon calls the “technical price”, and efforts devoted to moving the price away from the technical benchmark are largely irrelevant. When regulators can be captured instead (or they can blackmail firms), such negotiation efforts are likely to matter. Similarly, p(.) can be seen as a price net of certain costs over which procurement managers of the firm have power. When procurement managers can collude with providers and overcharge the firm, top managers of the firm may want to devote more effort at curbing overcharging and improving the net price for the firm. Thus, our model is compatible with at least two ways in which corruption can damage the efficiency of firms. One concerns external corruption—or the possibility that public officials are corrupt. The other concerns internal corruption—as when procurement by the firm is subject to abuse.

Our key assumption is,

: Higher corruption in the country increases the marginal return to effort in activities go other way from factor coordination 

This assumption captures the central element of our theory of diversion of managerial effort: in more corrupt countries, tasks that do not help the productive process are more rewarding at the margin.9 Note that corruption, however, need not lower nor raise profits (or other sources of managerial payoffs) for a given level of effort. When corruption takes the form of regulatory extortion or internal procurement abuse, profits will tend to suffer unless managers devote significant efforts to courting regulators or monitoring procurement officers. In other circumstances, such as those associated with active rent-seeking, corruption may mean that the regulator can be captured easily. In this case, for any level of effort, the firm’s profits are likely to be higher than otherwise. We remain agnostic regarding the effects of corruption on the level of profits. To abstract from these differences, we assume that, around equilibrium, 

Corruption investigators should be familiar, followed by their application to the proof of Corrupt  Practices.

Direct evidence, as the name implies, is evidence that tends to prove a fact directly – for example, a statement from an eyewitness or the cancelled check used for a bribe payment or a confession by the subject. Direct evidence is usually considered to be the strongest method of proof.

Circumstantial proof of “knowledge and intent”

Proof of knowledge and intent – proof, for example, that the subject knew that a document was forged and submitted it with the intent to defraud another party.